International Journal of Operational Research (163 papers in press)
Development of Maze Puzzle Algorithm for the Job Shop Scheduling
by Manhar Kagthara, Mangal Bhatt
Abstract: Maze Puzzle Concept has been introduced for solving job shop scheduling problem. Maze Puzzle Algorithm (MPA) is based on Rotation and Random Jumping which explores the solution space as well as exploits the solution near to optimum. Coding is done using MatLab software, Benchmark problem is evaluated for assessing efficiency of the algorithm. Results can be used for optimization of makespan for the given problem. The results are compared with other methods like GA, SA, SBI,SBII, PSO, BBO and TS, and found better than GA, SA, SB I, PSO, BBO but poor than SB-2 and TS.
Keywords: Maze Puzzle; Optimization; Job Shop Scheduling; Makespan; MATLAB; Jumping; Rotation.
Project Management Best Practices and Project Success in Developing Economies
by Saleh Fahed Alkhatib, Sarah Khrais
Abstract: This study aims to identify project management best practices, their impact relationships and their role in construction projects success in developing economies. Based on project experts semi-structured interviews, several project management best practices have been identified and validated. First, the DEMATEL technique is used to analyse the impact relationships between these practices and to classify them into
Keywords: Project Management Best Practices; Construction Projects; Project Success indicators; Developing Economies Projects; DEMATE Technique; Jordan.
Optimizing Preventive Maintenance Schedule for a Distillery Plant
by Ankur Bahl, Anish Sachdeava, R.K. Garg
Abstract: In today's era of automation, the maintenance of the complex systems is necessary for obtaining high payback ratios. The time has changed the thinking of plant/maintenance managers from fix-it-broken approach to preventive maintenance approach for bringing back the deteriorated components/systems to the predetermined operational conditions. But since the resources are limited therefore it is required to achieve an effective maintenance approach to minimise the total maintenance cost and equipment downtime. This paper presents the framework for deciding the optimal schedules for preventive maintenance under constraints of the maintenance cost, availability and revenue generation. The programming package Mathematica is used to solve the complex equations of the framework and finding optimal preventive maintenance schedule. The practical case of a distillery plant is considered is gauge the effectiveness of this approach.
Keywords: preventive maintenance; maintenance cost; availability; petri nets; optimum schedule.
Exact and heuristic methods to solve the two-machine cross-docking flow shop scheduling problem
by Imen Hamdi, Yosr Hazgui
Abstract: In this paper we study the two-machine cross-docking flowshop scheduling problem. Cross-docking is an innovative logistical strategy in which truck is unloaded from inbound (supplier) vehicles and directly loaded into outbound (customer) vehicules without storage in between or less than 24 hours. We aim to determine the schedules of the inbound and outbound trucks in the crossdock while minimising the makespan. This problem is known to be NP-hard in the strong sense. We propose a mixed integer linear programming (MILP) which is tightened by adding valid inequalities. Also, we develop some heuristic methods which are based on some known and new priority rules. Then, we report the results of computational experiments on randomly generated problems.
Keywords: Cross-docking; Scheduling; MILP; Heuristics.
Computing Pareto set in the criterion space for bicriteria linear programs using a single criterion software
by François Dubeau, Marie Emmanuel Ntigura Habingabwa
Abstract: In case of a mathematical programming problem with conflicting criteria, the Pareto set is a useful tool for a decision maker. Based on the geometric properties of the Pareto set for a bicriteria linear program, we present a simple method to compute this set in the criterion space. We describe completely the algorithm and analyse its complexity. We illustrate the method by solving in details two simple examples. It is important to observe that the method requires only a basic linear program solver.
Keywords: Bicriteria linear program; efficiency set; Pareto set; criterion space; weighted-sum.
Multi objective inventory model for material resource planning with uncertain lead-time
by Heibatolah Sadeghi, Anwar Mahmoodi
Abstract: MRP, in its original form, utilises deterministic lead-time. However, the lead-time uncertainty is a fact of life in most of production systems. Therefore, developing MRP to deal with lead-time uncertainty is of great importance to academics and practitioners. In this paper, the problem of supply planning is considered in a multi-period, multi-level assembly system in which each sub-level has several components whose lead-times are uncertain. A two-objective mathematical model is presented not only to provide the appropriate number of periods in POQ policy, but also to determine the planning lead-time of each sub-level component. The aim of the model is to minimise the expected total cost, and to maximise the customer service level. Furthermore, two metaheuristic algorithms, namely non-dominated sorting genetic algorithm-II (NSGA-II), and multi-objective particle swarm optimisation (MOPSO) are proposed to solve the model. Finally, numerical experiments are carried out to compare the effectiveness of the procedures.
Keywords: Supply planning; random lead-time; Customer service level; periodic order quantity; Multi-objective genetic algorithm.
Detailed scheduling distribution of real multi-product pipeline
by Asma Berrichi, Wassila Abdellaoui, Djamel Bennacer, Fouad Maliki, Latefa Ghomri
Abstract: We conducted an optimisation study on an Algerian multi-product pipeline that supplies market with fuels, through two fuel centres. The successive transport results under the diffusion effect, an interface between two products in contact, this interface is no marketable in any case and must be stored separately to the pure products. The number of interfaces depends mainly on the number of transported batches. Once the interface is at the end of the pipeline, and when the storage tanks reach the high level, the pumping is interrupted, a situation that can cause fuels shortage of on the market. The mixed integer linear programming 'MILP' formulation was able to respond to our problem and eliminate the high-level of mixture tanks constraint, by scheduling the multi-product pipeline, considering real operating conditions: Injection flow rate of each product, the products transport sequence, the imperative storage of the interface at the 2nd fuel centre, etc.
Keywords: multi-product pipeline; petroleum products; interfaces; MILP formulation.
A complete ranking of decision making units with interval data.
by Somayeh Khezri, Gholam Reza Jahanshahloo, Akram Dehnokhalaji, Farhad Hosseinzadeh Lotfi
Abstract: Interval data envelopment analysis (interval DEA) deals with the problem of efficiency assessment when the inputs and/or outputs of decision making units (DMUs) are given as interval data. This paper focuses on the problem of ranking DMUs with interval data. First, we define extreme efficient units, super efficiency score, the best and the worst efficiency (inefficiency) frontiers in the interval DEA context. Then, we propose a novel method based on the lower and upper super efficiency scores of a unit under evaluation and the distance of that unit to four developed frontiers. Our method ranks all efficient and inefficient units which is one of the main advantages of it. Our method uses several essential criteria simultaneously to rank units with interval data. These criteria increase the discrimination power of our proposed method. Potential application of this method is illustrated with a dataset consisting of 30 branches of the social security insurance organisation in Tehran.
Keywords: Data Envelopment Analysis; Interval DEA; Decision Making Units; Ranking.
Strategic Inventories in a Supply Chain with Downstream Cournot Duopoly
by Xiaowei Hu, Jaejin Jang, Nabeel Hamoud, Amirsaman Bajgiran
Abstract: The inventories carried in a supply chain as a strategic tool to influence the competing firms are considered to be strategic inventories (SI). We present a two-period game-theoretic supply chain model, in which a singular manufacturer supplies products to a pair of identical Cournot duopolistic retailers. We show that the SI carried by the retailers under dynamic contract is Pareto-dominating for the manufacturer, retailers, consumers, the channel, and the society as well. We also find that retailer's SI, however, can be eliminated when the manufacturer commits wholesale contract or inventory holding cost is too high. In comparing the cases with and without downstream competition, we also show that the downstream Cournot duopoly undermines the profits for the retailers, but benefits all others.
Keywords: Supply chain coordination; Game-theoretic modeling; Strategic inventories; Contracts; Cournot duopoly.
A chance constrained closed-loop supply chain network design considering inventory-location problem
by Mehdi Biuki, Hassan Mina, Parisa Mostafazadeh, Shiva Zandkarimkhani
Abstract: The design of reverse supply chain networks is one of the major solutions for the reduction of solid waste and use of resources for producing product to a lesser extent. The design of a reverse supply chain network leads to reduced costs in addition to reducing environmental detrimental effects. Therefore, this paper seeks to develop a mixed integer linear programming (MILP) model for designing a closed-loop supply chain network (CLSCN) under uncertainty. The under study network is multi-product, multi-period and multi-echelon wherein the possibility of storage and facing shortage in the back-order type has been considered. An approach based on chance constrained is applied for controlling uncertainty. In order to investigate the efficiency of the proposed model, we implemented it in an automotive manufacturing industry in Iran where the results of model implementation through real-world data in GAMS software, as well as the results of sensitivity analysis of demand values indicate the precise function and the accuracy of the results.
Keywords: Closed-loop supply chain; Inventory-location problem; Mathematical programming model; chance constrained theory.
Comparing Time-Stable Performance of Staffing Methods using Real Call-Center Data
by ARKA GHOSH, Dong Dai, Keguo Huang
Abstract: A central question in capacity management for service systems is to decide the number of servers that changes over time to accommodate time-varying arrivals and maintain a prescribed service-quality level. Two common methods for this are: square-root-staffing formula (SRSF) and iterative-staffing algorithm (ISA). We examine the stability of these two methods on simulated data from a probabilistic model and on a synthetic data created by resampling actual arrival, service and abandonment times from the call-centre of an Israeli bank. We use the delay probability as well as other common measures for the quality of service. In the simulated case, the ISA method marginally outperforms the SRSF method in maintaining the stability around the target delay probability. But in the case of synthetic resampled data, the stability drops when the service and patience rates are large. We also give theoretical proofs for the convergence of the ISA method under appropriate conditions.
Keywords: staffing; call-centers; capacity planning; re-sampling; data analysis; queues with time-varying arrivals.
Reliability optimization of parallel-series system with interval valued and fuzzy environment via GA
by Anushri Maji, Asoke Kumar Bhunia, Shyamal Kumar Mondal
Abstract: Reliability is an essential implement for a system. In this paper, we have considered a reliability optimisation problem in parallel-series system. Here, we have discussed about that how many components are needed to maximise the system reliability with some resource constraints such as cost, weight, volume, etc. Also, to get more relaxation we have assumed that the component reliabilities are interval valued number, lie between 0 and 1. Here, the constraint coefficients have been taken in fuzzy environment. Also, the fuzzy constraints have been defuzzified using possibility and necessity measures. The interval valued system reliability has been reduced to precise form applying centre-radius method. After reduction, our problem has been converted to a multi objective reliability optimisation problem with cost, volume, weight etc. as constraints. Finally, the proposed model has been illustrated numerically to study the feasibility of the system considering a real life example which has been solved by multi-objective genetic algorithm (MOGA).
Keywords: Parallel-series system; Interval valued component reliability; System reliability; Fuzzy constraint coefficients; Genetic algorithm.
Solving a Single Period Inventory Model with Fuzzy Inequality
by Anuradha Sahoo, J.K. Dash
Abstract: The purpose of this paper is to present a fuzzy chance-constrained single period inventory model (FCCSPIM) in which the fuzziness appears in the space constraint and objective function is crisp. Here the partial order relation exists in between a random variable and a real number. That means the probability of the event is discussed under vague data. Our approach for the solution process uses mostly fuzzy Zimmermann technique to convert the FCCSPIM into a proper deterministic equivalent. Then the resulting nonlinear deterministic model is solved by using LINGO software. The esult indicate that the fuzzy programming approach is effective for the inventory problem. The applications of an optimisation model under uncertainty are used to solve day to day problems. Many methods were developed by using tools of mathematics, probability theory and stochastic process. Here, one new approach of fuzzy programming technique is introduced to obtain a deterministic form.
Keywords: Single period inventory model; Chance constrained programming problem; Fuzzy partial order relation.
Selecting the most agile manufacturing system with respect to agile attribute- technology- Fuzzy AHP approach
by Ritu Chandna
Abstract: Agility of manufacturing systems is defined as the competence of existing and prospering in surroundings which are affected by continuous and unpredictable change and competition. Technology plays a vital role in helping managers to achieve agile manufacturing. Technology is changing rapidly and the manufacturing systems have to change their processes, structures, products and services accordingly to survive profitability in the market. Technology has four qualities which are knowledge about technology, finding direction in modern technology, ability in making technology more effective and a resilient method of bringing out technology. This paper uses fuzzy AHP approach to select the most agile manufacturing system with respect to these technological dimensions. This research will help decision makers to initiate technological innovations in manufacturing processes, to improve and help to control and evaluate the quality of emerging technologies and expand them for adoption. The analysis shows that flexible production technology parameter is more important as compared to other parameters.
Keywords: Agility; manufacturing system; technology; fuzzy AHP; competition.
Estimating Peppermint Oil Yields with Auxiliary Variable Information
by Dinesh K. Sharma, S.K. Yadav, Kate Brown
Abstract: In this article, we propose an improved method for estimation of the population mean using an auxiliary variable and apply it to the peppermint oil yield for a block level in the Barabanki District of Uttar Pradesh State in India. We consider a new family of estimators for the population mean, using the area of the peppermint field as the auxiliary variable. We study the sampling properties of the proposed family, through the bias and the mean squared error (MSE) to the first order approximation. We compare the suggested estimators with competing estimators theoretically and verify the conditions under which they outperform the competing estimators with actual data collected from the Siddhaur Block of the Barabanki District.
Keywords: Study Variable; Auxiliary variable; Regression-cum-Ratio estimator; Bias; MSE; PRE.
Development of IFDEA models for IF Input-oriented Mix Efficiency: Case of Hospitals in India
by Alka Arya, Shiv Prasad Yadav
Abstract: In conventional input-oriented mix efficiency (IOME), the input-output data are crisp numbers. But these data fluctuate in real world applications. Intuitionistic fuzzy set (IFS) theory can be used to to solve such problem. In this paper, models are proposed to determine intuitionistic fuzzy input-oriented mix-efficiency (IFIOME) with IF input and IF output data. For determining IFIOME, intuitionistic fuzzy input-oriented CCR (IFIOCCR) model and intuitionistic fuzzy input-oriented slack-based measure (IFIOSBM) model are proposed with IF input-output data. These models are solved by using expected values of intuitionistic fuzzy numbers (IFNs). Based on IFIOME, a ranking method is developed to rank the DMUs. Also, the intuitionistic fuzzy correlation coefficient (IFCC) between IF variables is proposed to validate the proposed models. To validate the proposed models, an illustrative example and a health sector application are presented.
Keywords: Data envelopment analysis; Intuitionistic fuzzy input-oriented CCR model; Intuitionistic fuzzy input-oriented SBM model; Intuitionistic fuzzy input-oriented mix-efficiency; Hospital efficiency.
Transient analysis of a Markovian N-policy queue with system disaster repair closedown setup times and control of admission
by T. Deepa, A. Azhagappan
Abstract: The main objective of this research work is to study the time-dependent behaviour of performance measures and probabilities for an M/M/1 queueing model with some interesting parameters such as closedown, setup periods, disastrous breakdown of the system, repair, N-policy and different control mechanism for the arrivals when the server is under repair as well as busy. In order to reduce the cost of production and to increase the profit, the manufacturing industries follow a technique of not to start the service until the number of work pieces reaches a fixed threshold value. Shutting down the machines when no jobs are available and setting up before the commencement of service play significant contributions to reach the goals in business organisations. The probabilities of the model under consideration are derived by the method of generating function for the transient case. Some system performance measures and numerical simulations are also presented.
Keywords: Markovian queue; N-policy; Disaster and repair; Closedown and setup times; Control of admission; Transient probabilities.
Analysis of state dependent M[X]/G(a, b)/1 queue with multiple vacation second optional service and optional re-service
by A. Azhagappan, T. Deepa
Abstract: The objective of this paper is to analyse an M[X]/G(a; b)/1 queueing model with second optional service, multiple vacation, state dependent arrival and optional re-service. After completing the first essential service, a batch of customers either requests for re-service or leaves the system without re-service. After the completion of first essential service (with or without re-service), the batch of customers either requests for second optional service or leaves the system. At the completion moment of the second optional service, the batch of customers either requests for re-service or leaves the system after the second service. Whenever the queue size is less than a, the server commences vacation. At the instant of vacation completion, if at least a customers wait for service, the server starts a busy period. Otherwise, the server resumes another vacation. Using supplementary variable technique, the steady-state probability generating function (PGF) of the queue size is obtained.
Keywords: Bulk queue; Second optional service; Multiple vacation; Optional re-service; State dependent arrival.
Optimal deductible and coinsurance policies under mean-variance preferences
by Christopher Gaffney
Abstract: We present a mean-variance analysis of optimal insurance coverage, showing how the relationship between the attitudes of the insured, in the form of their risk tolerance level, and the insurer, in the form of the insurance premium, affects insurance demand. Optimal parameter values (deductible, coverage limit, coinsurance level, and stop-loss limit) are derived, and we show that policies which include coinsurance and either a stop-loss limit or a deductible reduce to a straight deductible policy in the optimum. We also show that straight coinsurance is inferior to these policies.
Keywords: Insurance; Deductible; Coinsurance; Optimal Coverage; Mean-Variance.
Mathematical programming model to optimise an environmentally constructed supply chain: A genetic algorithm approach
by Rakesh Raut, Sejal Dhange, Vaibhav Narwane, Bhaskar Gardas, Balkrishna Narkhede, Niraj Dere
Abstract: The purpose of the study is to develop a network model for effective decision making from the sustainability aspect. The study proposes a mathematical programming model to optimise an environmentally constructed supply chain. The effect on the environment by components such as carbon monoxide, nitrogen dioxide and volatile organic particles formed during transportation in the supply chain has been considered. The multi-objective genetic algorithm optimises total cost and total environmental impact which were subjected to constraints of demand, return, flow balance, and capacity. The total cost consists of purchase cost, fixed cost, transportation cost, manufacturing cost, processing cost, and inventory cost. Environmental impact of production, transportation, handling, lead reclamation, and plastic recycling process was considered. The model also uses life cycle assessment-based method for quantification of environmental impact and establishes Pareto optimal solutions for minimisation of economic as well as environmental impact.
Keywords: Reverse logistics (RL); Closed-loop supply chain (CLSC); Environmental supply chain impact; Life cycle assessment (LCA); Battery Recycling; SLI Batteries; Multi-objective optimisation.
(s,S) Stochastic Inventory system in Jackson Network
by Md. Amirul Islam, Mohammad Ekramol Islam, Abdur Rashid
Abstract: In this work, we develop and analyze an (s,S) stochastic perishable inventory system at each node into Jackson network with a service facility in which the waiting hall for customers is of infinite size. Service times are exponentially distributed. We assume that demands arrive in the system according to a Poisson Process. Whenever the inventory level reaches the reorder level s an order Q units is placed to bring the level to S. The lead-time is exponentially distributed. The items of inventory have exponential life times. The joint probability distribution of the number of customers in the system and the inventory level is obtained in the steady state case. Matrix Analytical Method is applied to solve for the steady state occupancy probabilities. Various system performance measures in the steady state are derived. Numerical examples and graphical illustrations are provided to illustrate the proposed model.
Keywords: Jackson network; (s,S)-policy; Stability Condition; Performance analysis; Sensitivity Analysis.
Combinatorial Artificial Bee Colony algorithm hybridized with a new release of Iterated Local Search for Job-shop Scheduling Problem
by Amaria Ouis Khedim, Mehdi Souier, Zaki Sari
Abstract: Job shop Scheduling Problem (JSP) is recognized as an attractive subject in production management and combinatorial optimization. However, it is known as one of the most difficult scheduling problems. The present paper investigates the job shop scheduling problem in order to minimize the Makespan with a new hybrid combinatorial artificial bee colony algorithm. Firstly, the proposed combinatorial version integrates a Position Based Crossover for the updating of solutions and the Rank-Based Selection for selecting solutions to be updated in the onlooker bees phase. Another purpose of this study consists to highlight the impact of its sequential hybridization with a new release of iterated local search method called Simple Iterated Local Search (SILS). The proposed approaches are tested on many benchmark problems taken from the Operations Research Library (OR-Library). The simulation results show that the hybrid CABC performs the best in most of the studied cases.
Keywords: Job shop Scheduling Problem (JSP); Metaheuristics; Artificial bee colony Algorithm; Iterated Local Search.
Solving Multi-objective linear fractional programming problem based on Stanojevics normalization technique under fuzzy environment
by Indrani Maiti, Tarni Mandal, Surapati Pramanik, Sapan Kumar Das
Abstract: Fuzzy linear fractional programming (FLFP) problem has always been a subject of keen interest, and a rigorous research has also been done on it. However, due to some limitation of these methods, they cannot be applied for solving multi-objective linear fractional programming (MOLFP) problem with fuzzy coefficients and fuzzy variables. To overcome these limitations, Taylor series approximation and normalisation technique is applied in this problem. In this paper, we deal with the concept of ?-cuts which are employed to defuzzify the problem. We also formulate the membership function of each objective function is linearised using first order Taylor series approximation and normalisation technique. Normalisation technique is employed to ensure that the range of the reduced membership function belongs to [0, 1]. Then fuzzy goal programming is applied to solve the formulated problem so that the negative deviational variables are minimised. Finally, the fruitfulness of the proposed algorithm is illustrated through numerical examples as compared to other method.
Keywords: Fuzzy number; Fuzzy goal programming; Multi-objective linear fractional programming problem; Taylor series; Normalization; Crisp functions.
AN EFFICIENT METAHEURISTIC FOR DYNAMIC NETWORK DESIGN AND MESSAGE ROUTING
by Robert Hartlage, Jeremy Jordan
Abstract: As information requirements continue to increase, faster algorithms are necessary to effectively and efficiently deliver critical information across the Global Information Grid Given a list of required message traffic, to include source, destination, size, and priority, the idea is to design networks to maximize the delivery of message traffic based on message priority and quality of service, and then route the messages efficiently. Due to the dynamic nature of the problem and the combinatorial explosion in size as new network nodes are added, a quick-running heuristic approach is needed. In this research, a metaheuristic is developed to dynamically design the network based on the projected message traffic requirements and efficiently route the required messages on the network, based on priority, maximizing the number of messages successfully delivered and the quality of service of the delivery. The meta-heuristic is tested and generates high quality solutions quickly relative to current methods.
Keywords: Metaheuristics; Network Flows; OR in military; OR in telecommunications.
AN INTEGRATED APPROACH FOR EVALUATING THE ENABLERS FOR GREEN MANUFACTURING USING DEMATEL AND ANALYTIC NETWORK PROCESS
by Sandeep Handa, Tilak Raj, Sandeep Grover
Abstract: In recent decades increase in environmental awareness has motivated the manufacturers towards minimizing the use of exhaustible resources. Green manufacturing focuses on manufacturing technologies and initiatives that optimize energy usage and resource conservation. Green manufacturing aims to minimize environmental impact of manufacturing activities. The central objective of green paradigm is the combination of economic and ecological efficiency. This study aims to identify the key enablers for green manufacturing. The study uses an integration of Decision Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP). The analysis reflects the interdependencies among the enablers of green manufacturing. The results indicates that Customer demand, Implementing eco innovation and Availability of collaborative suppliers are the top three enablers for the transition towards green manufacturing.
Keywords: Green Manufacturing; Enablers; DEMATEL; ANP.
An exact approach to the integration of noncyclical preventive maintenance scheduling and production planning for a series
by NIZAR E.L. HACHEMI, Mohammed Anouar Jamali, Abdessamad AitElCadi, Louis Martin Rouseau, Abdel Hakim Artiba
Abstract: In this paper, we generalise a model for integrated noncyclical preventive maintenance scheduling and production planning from a single machine to a series-parallel production line. As for a single machine, we consider a set of products that must be produced in lots during a given time horizon. The maintenance strategy involves possible preventive replacements at the beginning of each maintenance period and minimal repair at machine failure. The model, an integer linear program, determines the optimal production plan and preventive replacement for each machine of the production line. The objective is to minimise the total cost (preventive and corrective maintenance costs, setup costs, holding costs, backorder costs, and production costs) while meeting the demand for each product over the horizon. We performed experiments using CPLEX 12.5.1, and almost all instances were solved within five minutes with a reasonable gap.
Keywords: Production planning; noncyclical preventive maintenance; linear programming; branching strategies; series-parallel system.
An innovative hybrid fuzzy TOPSIS based on Design of Experiments for multi criteria supplier evaluation and selection
by Mohammad Reza Marjani, Mohammad Habibi, Arash Arash Pazhouhandeh
Abstract: In this article, nine important criteria are considered to select the best supplier in supply chain risk management. For this purpose, to address the unspecified criteria and the results analysis, the combination approach of fuzzy TOPSIS and Design of Experiments (DOE) were presented and a 2k factorial design for factor analysis was used at two low and high levels. Combining the Fuzzy TOPSIS and Design of Experiments, gives the decision makers more freedom to select, because it can analyze the effects of different factors on the response variable by sensitivity analysis and according to different weights defined by each decision maker, obtain different results and compare them. In addition, for the ranking of the factors based on each response variable, the Pareto chart was used and the ineffective factors were eliminated. Finally, the ranking results for each decision maker were compared with Shannon entropy weight modification method and decision makers.
Keywords: supplier selection; supply chain risk management; fuzzy TOPSIS; design of experiments; DOE; 2k factorial design; Pareto chart; Shannon entropy; Analysis of variance; ANOVA; grey TOPSIS.
USING CRITERION BASED MODEL AVERAGING IN TWO-INPUT MULTIPLE RESPONSE SURFACE METHODOLOGY PROBLEMS
by Domingo Pavolo, Delson Chikobvu
Abstract: Experimental designs in multiple response surface methodology (MRSM) often result in small sample size datasets with associated modeling problems. Classical model selection criteria are inefficient with small sample size datasets and sample sizes below (10+k), where k is the maximum number of regressors inclusive of the intercept, suffer from credibility while the model selection process has inherent uncertainty. In this empirical paper, criterion based frequentist model averaging (CBFMA) is investigated as a solution to the problems of modeling MRSM datasets. We also compare the accuracy of process optimisation using CBFMA models versus ordinary least squares (OLS) candidate models. Findings suggest CBFMA models produce effective and accurate results and solve the small sample size model selection criteria bias problem. However, in the MRSM context, CBFMA does not directly solve the model selection uncertainty problem and averaged model estimators have mean squared errors that are greater than the best OLS candidate models.
Keywords: Multiple Response Surface Methodology; Experimental design; All Possible Regression Models; Frequentist Criterion Based Model Averaging; Small Sample Size Datasets; Process optimisation.
Application of a Mobile Facility Routing Problem in a delivery company
by Sonia Avilés-Sacoto, Osmar Salvador-Grijalva, Galo Mosquera-Recalde
Abstract: Nowadays e-commerce business has created new distribution channels to reach customers. This setting includes policies and changes in the delivery process, such as small orders, short delivery schedules, and variables workloads. One approach to meet these requirements is mobiles facilities, which place products closer to customers with known location and product requirements. However, finding out the right position for the mobile facilities considering time and demand variability constitutes a challenge. This study proposes a methodology to determine the location and time where mobile facilities should be to optimize the delivery of products. Several tools such as clustering, routing problem optimization, and Monte Carlo simulation are combined with the aim to minimize the transportation costs associated to the delivery of the products and the cost associated to the unmet demand. A real case study is presented with the optimal route for two mobile facilities for a 15-minutes time window.
Keywords: Mobile Facility; Routing Problem; Monte Carlo Simulation; Clustering; Delivery; Transportation; Costs; Vehicles; Demand; Strategic Points; Time window.
An EOQ model for non-instantaneous deteriorating items with time-dependent quadratic demand and two-level pricing strategies under trade credit policy.
by Babangida Bature, Yakubu Mamman Baraya
Abstract: In this paper, an EOQ model for non-instantaneous deteriorating items with two phase demand rates and two-level pricing strategies under trade credit policy is considered. It is assumed that the unit selling price before deterioration sets in is greater than that after deterioration sets in. Also, the demand rate before deterioration sets in is assumed to be continuous time-dependent quadratic and that after deterioration sets in is considered as constant and shortages are not allowed. The main purpose of this research work is to determine the optimal cycle length and corresponding economic order quantity such that the total profit of the inventory system is optimise. The necessary and sufficient conditions for the existence and uniqueness of the optimal solutions are established. Numerical examples are given to illustrate the theoretical result of the model, Sensitivity analyses of some model parameters on the decision variables were carried.
Keywords: economic order quantity; non-instantaneous deteriorating items; time-dependent quadratic demand rate; two-level pricing strategies; trade credit policy.
Hierarchical learning model for early prediction of coronary artery atherosclerosis
by Muruganantham Sowmiya, B. Banu Rekha, Elangeeran Malar, K.R. Ashwin Kumaran
Abstract: Drastic improvement in the field of science and technology have made the lives of humans more sophisticated. As a result, physical activities in which the people indulged have reduced and this has made them prone to Coronary Artery Disease (CAD). Coronary Artery Atherosclerosis (CAA) is one of the main causes of CAD and therefore, early prediction of CAA is indispensable to prevent the risk of people getting affected by CAD and sudden deaths. This work presents the machine learning model which provides more information on the exceptional cases while retaining the existing traditional classifier model. The proposed model performs outliner detection using Local Outlier Factor (LOF) and class balancing using Synthetic Minority Oversampling Technique (SMOTE). Genetic algorithm is used for prominent feature selection and utilizes Support Vector Machine (SVM) and Neural Network (NN) as classifier. UCI and South African Heart disease datasets are used to implement the proposed model.
Keywords: Machine learning; support vector machine; neural network; local outlier factor; feature selection.
Octanary Polyhedral Branch and Bound for Integer Programs
by James P. Bailey, Todd Easton, Fabio Vitor
Abstract: This paper introduces the octanary branching algorithm (OBA), a polyhedral branching technique to solve integer programs. Unlike the traditional branch and bound algorithm, each of OBA's branching nodes generates eight children instead of two. Four of them are created by equality constraints, while the other four use inequalities. This branching strategy allows a dimension reduction of the linear relaxation space of the four equality children, which should enable OBA to find quality integer solutions sooner than the branch and bound algorithm. Computational experiments showed that the branch and bound algorithm required over one billion nodes to identify a solution that is at least as good as the solution found by OBA after only half a million nodes. Consequently, OBA should replace the branch and bound algorithm during the first portion of the branching tree, be used to identify a warm start solution, or be implemented as a diving strategy.
Keywords: Branch and Bound; Hyperplane Branching; Branching Polyhedra; Random Diving; Integer Programming.
Fuzzy multi-objective programming for supplier portfolio formation: A credibility based approach
by Garima Mittal
Abstract: In a multiple-sourcing environment, supplier selection plays an integral role in efficiently managing a supply chain of an organization. This paper proposes a fuzzy multi-objective programming model using a credibility measure, for forming a portfolio of suppliers. Credibility measure has an advantage of self-duality over more prevalent possibility measure. In this paper credibility measure of a fuzzy event is used to model the three objectives of minimizing expected cost, maximizing expected quality and maximizing the expected on-time delivery, along with other realistic constraints that are integral part of the supplier selection problems. The proposed credibilistic model is solved using a fuzzy goal programming approach that has then been extended to three different scenarios in order to address decision maker's satisfaction with respect to the achievement level of the various objectives. A numerical illustration is also provided to depict the utility of the proposed model and approach.
Keywords: Fuzzy supplier portfolio; Expected value model; Fuzzy multi-criteria decision making; Credibility measure; Fuzzy goal programming; Supplier selection.
A Multiple Criteria Decision Making improvement strategy in complex manufacturing processes
by Soltani Mohyiddine, AOUAG Hichem, Mouss Mohamed Djamel
Abstract: The purpose of this paper is to propose an improvement strategy based on multi-criteria decision making approaches, including fuzzy analytic hierarchy process (AHP), preference ranking organisation method for enrichment evaluation II (PROMETHEE) and viekriterijumsko kompromisno rangiranje (VIKOR) for the objective of simplifying and organising the improvement process in complex manufacturing processes. Firstly, the proposed strategy started with decision makers selection including leaders company to determine performance indicators. Than fuzzy AHP is used to quantify the weight of each defined indicators, finally, the weights carried out from fuzzy AHP approach are used as input in VIKOR and PROMETHE II to rank the operations according to their improvement priority. The results obtained from each outranking method are compared and the best method is determined.
Keywords: analytic hierarchy process (AHP); VIekriterijumsko KOmpromisno Rangiranje (VIKOR); Fuzzy Logic; PROMETHE; improvement priority; Complex manufacturing process.
Multi-Criteria Optimization of Fire Station Location in Gaza Strip
by Abdelrahman Abuserriya, Sadiq Abdelall, Salah Agha
Abstract: Fire stations along with their locations in Gaza Strip are extremely important because of the political situation This paper evaluated fire stations locations and suggested how to improve their performance in Gaza Strip The paper uses two models, these models include set covering and goal programing models, the models were solved in two stages: the first stage used the set covering model to determine the number of fire stations needed for given time limits (6, 8 minutes) The output of the first model was inputted into second model to determine the locations of fire stations Further, several scenarios were proposed for sensitivity analysis The first scenario freely identified the locations of each fire station, while the second scenario was forced model to select/unselect given locations based on decision makers preferences Based on fire department request which called for expansion through identifying the optimum number and locations of new fire stations.
Keywords: fire stations location; goal programing; Gaza Strip; multi criteria; set covering.
Optimal Production Output and Frequency of Rest-Breaks for a Worker Subjected to Fatigue
by Mohammed Darwish, Khaled Alali, Adel Alshayji
Abstract: It is reported by many researchers that the quality of produced items deteriorates and work-related incidents increase when a worker is subjected to high level of fatigue at workplace. As a direct consequence, the daily production yield of the worker decreases which, in turn, reduces the profit of a company. Some authors suggested short breaks at workplace so that the worker overcomes fatigue and improve productivity. In this paper, we mathematically study this relationship and develop a model that finds the optimal work-rest schedule such that the daily production output of a worker is maximized. We assume that the worker fatigue increases exponentially during work. Unlike the models used in the literature, the reduction in the worker fatigue level is modeled by utilizing concepts in the preventive maintenance engineering literature. This simplifies the solution method significantly.
Keywords: Operations research; production; worker safety; rest-breaks; worker fatigue; exponential fatigue function.
BRANCH AND BOUND TECHNIQUE FOR TWO STAGE FLOW SHOP SCHEDULING MODEL WITH EQUIPOTENTIAL MACHINES AT EVERY STAGE
by SONIA GOEL, Deepak Gupta
Abstract: This paper is an attempt to schedule n-jobs on two machines with parallel equipotential machines at every stage. The operating costs of all jobs on all parallel equipotential machines are given. The dispensation time of all the jobs on all the two machines is given and the time for which parallel equipotential machines are available is also known. The purpose of this work is to find the best possible schedule of jobs with the intention to diminish the entire elapsed time. The algorithm developed is illustrated with the help of example.
Keywords: Scheduling; Elapsed time; equipotential machines; operating cost.
Optimizing Fully Fuzzy Interval Integer Transshipment Problems
by A. Akilbasha, Pandian Ponnaiah, Natarajan G
Abstract: In this paper, we focus on solving fully fuzzy interval integer transshipment (FIIT) problems where the unit shipping costs, available supply capacities, and required destination demands are triangular fuzzy interval integers. An innovative method namely, back order sequence method has been developed for finding an optimal solution of the fully FIIT problem. The proposed method provides that the optimal values of decision variables and objective function value for the fully FIIT problem are fuzzy interval integers. A numerical example is presented to illustrate the solution procedure of optimizing fully FIIT problems. The optimal solution to the transshipment problem by the proposed method can help the managers to take an appropriate decision regarding transshipments.
Keywords: Interval; Fuzzy set; Fuzzy interval; Transshipment problem; Optimal solution; Back order sequence method.
In-House Production vs Outsourcing: the Effect of Volume-Based Learning on Quality Competition
by Yanni Ping, Seung-Lae Kim
Abstract: This paper considers an original equipment manufacturer (OEM) who outsources finished products to a contract manufacturer (CM), who adopts the OEMs existing technology and achieves quality improvement through learning-by-doing. Besides the role of upstream partner, the CM also becomes a downstream competitor. We examine learning-by-doing and quality dynamically under a two-period model both for cases when quality competition exists and does not exist. We identify the conditions under which pure outsourcing, partial outsourcing, or non-outsourcing is most advantageous. When there is no quality competition and when the CMs quality improvement does not hurt the OEMs future demand, we find that it would still be beneficial for the OEM to apply a partial outsourcing strategy. When quality competition exists, the OEMs decision in the second period follows the same pattern as the non-competition case, while the CMs wholesale price depends on the trade-off between selling through the OEM and selling independently.
Keywords: learning-by-doing; outsourcing; quality-improvement; competitive CM.
Research on Optimal Product Supply Strategies for Manufacturer-to-Group Customer under a Real Demand Pattern
by Zhiyi Zhuo
Abstract: In a product supply chain, customer demand determines the market and supply as well as the benefits accruing to manufacturers and retailers. Customer demand has three different patterns: real, false, and semi-real. This paper develops a mathematical model to investigate the factors that determine manufacturers design and plan of product supply strategies for group customers under the real demand pattern and solve for maximum profit. We use numerical examples to verify the validity of the model. This papers contribution is the construction of two mathematical models for off-invoice mode and unsold recycling mode of manufacturer-to-group customer product supply strategies under a real demand pattern.
Keywords: Real demand pattern; Product supply strategies; Profit function; Optimal method.
A Complete Information PCA-Imprecise DEA Approach for Constructing Composite Indicator with Interval Data: an Application for Finding Development Degree of Cities
by Hashem Omrani, Kolsoom Zamani
Abstract: Composite indicator approach is widely used for finding development degree of regions.This paper presents a complete information principal component analysis (CIPCA)-Imprecise data envelopment analysis (IDEA) approach for finding development degree of cities with uncertain data. CIPCA is applied to reduce the number of indicators. The output of the CIPCA is a set of new indicators with lower and upper bounds. These indicators are considered as indicators of IDEA and final ranks of cities are calculated by IDEA model. To illustrate the capability of CIPCA-IDEA approach, the development degrees of cities in Kurdistan province of Iran are calculated. First, 62 development indicators are selected and the related interval data for year 2015 are gathered. Then, the proposed approach is applied for nine cities of Kurdistan province and development degree for each city is finally calculated. The results indicate that in the overall ranking, Bijar city is top ranked.
Keywords: Composite indicator; CIPCA; IDEA; Development degree.
Development of a Heuristic for No-Wait Flowshop Production Process to Minimize Makespan
by Azahar Alam
Abstract: No-wait flow shop production system has much practical application in manufacturing industries. Minimisation total completion time of no-wait flow shop comes under the NP-complete category. Consequently, getting effective and efficient quality of result for such types of problems is a challenge where effective means optimal or near-optimal solution and efficient means which taking less computational time. A heuristic is proposed for the problem under consideration, in which problem is getting solved in two phases. The first phase is the initial sequence generation, and the second one is the improvement phase. Proposed heuristic is compared with four best-known heuristics, and for smaller size problem exhaustive enumeration is used to check the performance of the heuristic. Moreover, heuristic performance is tested over 600 randomly generated problem of different sizes. For large size problem, it showed that proposed heuristic is very much efficient.
Keywords: Heuristic; No-wait flowshop problem; Makespan minimisation; Computational complexity.
JACKKNIFING THEN MODEL AVERAGING: Investigating the Improvements to Fitness to Data and Prediction Accuracy of Two-Input Under- and Just-Fitted Response Models
by Domingo Pavolo, Delson Chikobvu
Abstract: The possibility of improving the fitness to data and prediction accuracy of models in a multi-response surface methodology environment of under and just-fitted ordinary least squares response models by jackknifing then combining the resultant partial estimates and the pseudo-values using arithmetic averaging or criterion-based frequentist model averaging was investigated. Jackknifing is known to reduce parametric and model bias. Model averaging is known to reduce model bidirectional bias and variance. A typical multi-response surface methodology dataset and resultant validation dataset were used as example. Results suggest that it is possible to obtain better fitness to data and prediction accuracy by jackknifing a just-fitted response model of interest and combining the resultant partial estimates using arithmetic averaging. The combining of pseudo-values using arithmetic averaging or criterion-based frequentist model averaging gave mixed results. The actual jackknife model estimators gave good performance with under-fitted models.
Keywords: KEY TERMS: multiresponse surface methodology; jackknifing; partial estimates; pseudo-values; arithmetic model averaging; criterion-based frequentist model averaging.
A Lower Bound Competitive Ratio for the Online Stochastic Shortest Path Problem
by Mohsen Abdolhosseinzadeh
Abstract: In the online networks, some parameters are not known for decision makers in prior, especially the arc costs are revealed over time; so, the online decisions should be made without complete knowledge of the future events. Three kinds of statistical information are available by arrival the last traversed nodes in an online manner: the exact traversed length, the average shortest path length and the shortest path length. So, three different stochastic models are considered and the related stochastic online decision criteria are obtained, such that the best competitive ratio is 2.3130. Again, it is assumed that the online decision maker is informed about the intervals of the arc costs; then, some constant competitive ratios are produced and 2.3130 determined as the best obtained lower bound competitive ratio against some previous works.
Keywords: Online stochastic network; Online decision problem; Competitive analysis; Online stochastic shortest path.
Production Planning and Scheduling with Applications in the Tile Industry
by Armindo Soares, Carina Pimentel, Ana Moura
Abstract: In this paper we consider the medium to short term production planning and scheduling (PPS) process of a ceramic tile industry. The PPS process encompasses three problems: (1) the development of a master production plan that determines the medium-term production needs; (2) the development of a biweekly production scheduling plan that minimizes the production time required to complete the set of products, so as to meet customer orders within agreed due dates and ensure the filling of connected firing kilns; and (3) the available-to-promise problem. The production scheduling problem (PSP) was addressed as an identical parallel machine problem, with machine eligibility constraints, family and subfamily setups and minimum production lot sizes. A specific heuristic and a mixed integer programming model are proposed to solve the PSP. A model-driven decision support system, that improves the quality and time expenditure of the PPS process, is also presented.
Keywords: production planning and scheduling constructive heuristic decision support system mixed integer programming tile industry master production schedule available to promise production scheduling.
Detection of the Diffusion Nanoparticle in the Turbulent Flows Using the Random Walk Model
by Mohamed El-hadidy
Abstract: A probabilistic detection model is proposed to determine the location of random walk nanoparticles in the turbulent flows. This model maximises the benefits for the environmental, industrial and biological applications. In this paper, we present a generalised coordinated linear detection technique to find a one-dimensional random walk nanoparticle between two layers in turbulent flows. We have two sensors start the searching process from any point rather than the origin. The initial position of the nanoparticle is a random variable that has a known probability distribution. More than showing the existence of a finite search plan, we derive some auxiliary results related to optimal search plan which minimises the expected value of the first meeting time between one of the sensors and the nanoparticle. A numerical example is provided to illustrate the effectiveness of this technique.
Keywords: Turbulent flows; Random Walk nanoparticle; Probability space.
Solving the Team Orienteering Problem with Time Windows and Mandatory Visits Using a Constraint Programming Approach
by Ridvan Gedik, Emre Kirac, Furkan Oztanriseven
Abstract: This paper presents a constraint programming (CP) approach for solving the team orienteering problem with time windows and mandatory visits (TOPTW-MV), which has many real-world implementations, such as tourist tour planning, routing technicians, and disaster relief routing. In the TOPTW-MV, a set of locations is given; some locations must be visited, while others are optional. For each location, the profit, service time, and service time window information are known. A fleet of homogeneous vehicles is available for visiting locations and collecting the profits. The objective in solving this problem is to create a set of vehicle routes that begin and end at a depot, visit mandatory locations exactly once and optional locations at most once, while observing other restrictions such as time windows and sequence-based travel times. The CP-based approach finds 99 of the best-known solutions and explores 64 new best-known solutions for the benchmark instances.
Keywords: Team orienteering problem; time windows; mandatory visits; vehicle routing; constraint programming; CP; optimization.
Distribution and inventory planning in multi-echelon supply chains under demand uncertainty
by Joaquim Jorge Vicente, Susana Relvas, Ana Barbosa-Póvoa
Abstract: Distribution and inventory planning in a multi-echelon system are studied under an uncertain demand context. To deal with this problem a mixed integer linear programming (MILP) model is proposed. This considers a multi-echelon system formed by N-warehouses and M-retailers. The problem consists on determining the optimal reordering plan for the operating network, which minimises the overall systems operation cost. The uncertain demand faced by retailers is addressed by defining the optimal safety stock that guarantees a given service level at each regional warehouse and each retailer. Also, the risk pooling effect is taken into account when determining inventory levels in each entity. A case study based on a real retailer distribution chain is presented and solved.
Keywords: supply chain management; inventory planning; mixed integer linear programming; MILP; guaranteed service approach; demand uncertainty; risk pooling.
A tri-level mixed-integer program for the optimal fortification of a rail intermodal terminal network
by Manish Verma, David M. Tulett, Hassan Sarhadi
Abstract: Rail-truck intermodal transportation plays an important role in moving freight in North America, and hence the availability and appropriate functionality of the associated infrastructure is crucial. To this end, one of the strategies to mitigate (minimize) the adverse impacts from (intentional/random) disruption prescribes fortifying a set of rail intermodal terminals so that continuity in its service is ensured. In this paper, we re-visit the tri-level model to protect a given number of rail intermodal terminals such that the effect of worst-case disruptions is minimized. We propose a tabu search metaheuristic to solve the outer level problem, and then combine it with a decomposition-based technique to solve the entire model. The proposed methodology is tested on the problem instances introduced in an earlier work, and to comment on the computational efficiency vis a vis the existing techniques in the literature.
Keywords: intermodal transportation; mixed-integer program; fortification; tabu-search metaheuristic; decomposition.
The problem of detecting nonlinearity in time series generated by a state-dependent autoregressive model. A simulation study
by Fabio Gobbi
Abstract: The aim of the paper is to try to measure, through a Monte Carlo experiment, nonlinearity in time series generated by a strictly stationary and uniformly ergodic state-dependent autoregressive process. The model under study is intrinsically nonlinear but the choice of parameters strongly impacts on the type of serial dependence making its identification complicated. For this reason, the paper exploits two statistical tests of independence and linearity in order to select the parameter values which ensure the joint rejection of both hypothesis. After that, our study uses two measures of nonlinear dependence in time series recently introduced in the literature, the auto-distance correlation function and the autodependence function, in order to identify nonlinearity induced by the proposed model.
Keywords: nonlinear time series; independence test; linearity test; auto-distance correlation; autodependogram.
Real Coded Self-Organizing Migrating Genetic Algorithm for nonlinear constrained optimization problems
by Avijit Duary, Nirmal Kumar, Md. Akhtar, Ali Akbar Shaikh, Asoke Kumar Bhunia
Abstract: The objective of this article is to propose a new hybrid algorithm named as real coded self-organising migrating genetic algorithm (C-RCSOMGA) by combining real coded genetic algorithm (RCGA) and modified self-organising migrating algorithm (SOMA) for solving the nonlinear constrained optimisation problems. In RCGA, a modified mutation operator called as double mutation operator has been introduced combining two different existing mutation operators, whereas in SOMA, a modified strategy has been proposed. To test the performance of the proposed algorithm, a set of test problems taken from the existing literature has been solved and the simulated results have been compared numerically as well as graphically with the existing algorithms. In the graphical comparison, a modification of performance index (PI) has been made. Finally, with the help of modified performance index (MPI), it has been shown that the proposed hybrid algorithm has performed much better than the existing algorithms.
Keywords: genetic algorithm; self-organising migrating algorithm; SOMA; performance index; nonlinear constrained optimisation; global optimisation.
Aggregate Production Planning of Abu Ghraib Dairy Factories based on Forecasting and Goal Programming
by Wakas Khalaf, Mustafa G. Ali
Abstract: The aim of this article is to build a comprehensive multi-objective production plan for Al-Rafidain plant spanning 12 months based on two methods the auto regression integrated moving averages (ARIMA) model to forecast the market demand for the products and the method of goal programming (GP) to find compatible solutions among the goals to be achieved. The ready-made program MATLAB was used to find the future values of the time series and also to solve the multi-objective mathematical model. For the most important results achieved, the mathematical model was able to achieve the first goal by 97%, which was the maximisation of profits; the total profits achieved a value of USD3,625,856. The second goal was achieved successfully because of the decrease that occurred in the costs, the value of which was USD2,456,625. Finally, the third goal was achieved by 98%, in that the plants return on investment was decreased to 1.476.
Keywords: aggregate production planning; APP; goal programming; forecasting; auto regression integrated moving averages; ARIMA.
Multi-objective optimization for solving cooperative continuous static games using Karush
by PAVAN KUMAR, Hamiden Abd El- Wahed Khalifa
Abstract: This paper introduces cooperative continuous static games (CCSG) with parameters in the cost functions of the players and in the right-hand side of the constraints. The CCSG is converted into the corresponding multi-objective nonlinear programming problem. The resulted nonlinear programming problem is converted into the single objective nonlinear programming problem through the use of the weighted sum method. A solution method for obtaining the stability set of the second kind without differentiability for the CCSG is presented using Karush-Kuhn-Tucker conditions. A numerical example is given for the illustration.
Keywords: Cooperative continuous static games; Efficient solution; Weighted sum method; optimal solution; Karush-Kuhn-Tucker conditions; Stability.
Optimization of finite Economic Production Quantity Model Under Cloudy Normalized Triangular Fuzzy Number
by Neelanjana Rajput, R.K. Pandey, Anand Chauhan
Abstract: This study introduced economic production quantity (EPQ) model with a finite production rate is established for cloudy normalised triangular fuzzy number (CNTFN). In real-life situations, the goals and inventory parameters are may not precise. Such type of uncertainty may be characterised by fuzzy numbers. The main object of this research effort is to develop a mathematical model and optimise EPQ with different environment like crisp, general fuzzy and cloudy fuzzy situations. A novel defuzzification methodology has been used for EPQ by Yagers ranking index method. Here, the constraint goal and the inventory cost parameters are assumed to be triangular-shaped fuzzy numbers with different types of left and right membership functions. The cost functions associated to these models are verified to be convex and optimal criteria are established in all three situations. The models are numerical, graphically demonstrated and sensitivity analysis shows a decent explanation. Also, discuss the applications and future scope of the CNTFN model in realistic situations such as when items are not easy to replenish due to some transport problem and some problems in geographically hilly regions, how to use cloudy fuzzy number
in that situations.
Keywords: fuzzy optimisation; decision making; cloud fuzzy number; EPQ inventory model; finite production; extended Yager’s ranking index method.
Misspecification of Data Envelopment Analysis
by KEKOURA SAKOUVOGUI
Abstract: Data envelopment analysis (DEA), a non-parametric efficiency estimator uses linear programming technique for the computation of estimates of decision-making units, such as, universities, schools, hospitals, banks, or mutual funds. There has been an ongoing debate about the application of the DEA model for model misspecification and in particular the inefficiency error of production for input and output variables. This paper contributes to this debate by examining several misspecifications of the DEA model in Monte Carlo (MC) simulations. MC simulations are conducted to examine the performance of the DEA model under two different data generating processes, stochastic and deterministic, and across five different misspecification scenarios, inefficiency distributions (traditional and proposed approaches), sample sizes, production functions, input distributions, and curse of dimensionality.
Keywords: data envelopment analysis; DEA; inefficiency distributions; Monte Carlo simulations.
Markov manpower planning models: a review
by Virtue Ekhosuehi, Vincent A. Amenaghawon, Augustine Osagiede
Abstract: A manpower system is a network of individuals working together in an organisation for the purpose of achieving the common goal of the organisation. To ensure that the right number of individuals is available to meet the task to be performed by the organisation, manpower planning techniques are needed. This paper reviews the manpower planning literature with specific interest on manpower systems modelled within the Markov chain context. Markov chains provide a convenient framework to: analyse the structural mechanisms, which underlie social change, and extrapolate shifts in the state distribution of the system; control personnel structures by framing optimal promotion and recruitment strategies; evaluate personnel policies; and deal with heterogeneity and uncertainty in the system configuration. This paper surveys these applications areas and highlights the methodological issues arising from varying the unit interval of the Markov manpower system in discrete time.
Keywords: embeddability problem; heterogeneity; manpower planning; manpower system; Markov chain; personnel structure; stochastic matrix; sub-stochastic matrix; transition matrix.
Agent-based modelling in Capacitated Lot Sizing Problem with Sequence dependent Setup time
by P. Raghuram
Abstract: Setups are indispensable in production, but consume substantial amount of productive time It is vital to consider sequence dependent setup times for determining production lots to satisfy demand for diversified product types on parallel production lines Optimisation is the most used technique to generate detailed schedules for such sequencing problems But the feasibility of the solution is not guaranteed under uncertainty conditions Thus, evaluating the solution configurations under uncertainty is necessary to confirm feasibility In this paper, an agent-based, discrete event simulation technique is used to develop a flowshop model which faces demand for multiple product varieties, and has sequence dependent setup time The simulation aims at evaluating various results in the solution space of an optimisation model to check their feasibility under various uncertain conditions in the form of setup time, processing time, and demand Results indicate that uncertainty influences overtime cost, holding cost, and lost sales.
Keywords: Agent-based modelling; capacitated lot sizing model; flow shop scheduling; optimization; simulation.
THE USE OF MOBILE APPLICATION TO BUY INSURANCE: AN AHP BASED STUDY
by Lav Ishan
Abstract: The Indian insurance industry is moving towards integrating the latest technology in their business activities, as this can help in increasing the companys efficiency. The use of mobile is high among the current generation, using this platform by insurance companies as a part of their business activities can help the company in many ways. This paper focuses on the use of mobile software by the customer and what are the factors which drive its use. Quantitative data were collected using questionnaire and interview of the respondent was taken to get an in-depth perspective regarding the mobile application. It was found out that the mobile application of insurance companies is used less by the customers and the way of increasing the use of the application is discussed. Findings can help the companies in determining how they can popularise their companys mobile application among their existing and targeted customers.
Keywords: Indian Insurance Industry; Insuretech; Multi-Criteria Decision Making; Analytical Hierarchal Process.
Multi-resource balancing: A case of a German kitchen manufacturer
by Sina Glaeser, Christian Ullrich
Abstract: We address a multi-resource balancing-problem at Nobilia-Werke J. Stickling GmbH & Co. KG, the leading kitchen manufacturer in Germany. Nobilia maintains no warehouse for finished goods. The customised cabinets of a kitchen are manufactured in parallel and aggregated just in sequence for loading into trucks immediately after production. A smooth flow of materials is essential to ensure on-time completion and loading of a whole kitchen. Nowadays, changing customer tastes drive customisation. Due to an increasing number of capacity restrictions in its production processes, Nobilias current planning method has reached its limits. We present an integer programming model to address a variant of the multi-resource generalised assignment problem (MRGAP). We consider a multi-criteria objective function and a set of constraints reflecting Nobilias requirements. We propose a software-based solution approach for Nobilias instance sizes. The results of our computational experiments on real-world data demonstrate that our approach provides significant benefits.
Keywords: resource balancing; integer programming; multi-criteria; production planning; machine assignment; mass customisation; generalised assignment problem; GAP; real-world application; LINGO.
Numerical Optimization of Loss System with Retrial Phenomenon in Cellular Networks
by Vidyottama Jain, Raina Raj, Dharmaraja Selvamuthu
Abstract: In this study, we extend upon the model by Haring et al. [IEEE Trans. Veh. Technol. 50, 664-673 (2001)] by introducing retrial phenomenon in multi- server queueing system. When at most g number of guard channels are available, it allows new calls to join the retrial group. This retrial group is called orbit and can hold a maximum of m retrial calls. The impact of retrial over certain performance measures is numerically investigated. The focus of this work is to construct optimization problems to determine the optimal number of channels, the optimal number of guard channels and the optimal orbit size. Further, it has been emphasized that the proposed model with retrial phenomenon reduces the blocking probability of new calls in the system.
Keywords: Multi-server queueing model; retrial phenomenon; cellular network; blocking probability; optimization.
A Strategic Donor-Beneficiary Assignment Problem under Supply and Demand Uncertainties
by JYOTIRMOY DALAL
Abstract: Considering the coexistence of food insecurity and food waste issues in the society, in collaboration with an NPO in India, we develop a novel donor-beneficiary strategic assignment model to connect the students of a set of volunteering schools with a set of habitats with under-nourished children up to 14 years of age, via a social-awareness-raising long-term endeavor. Our two-stage stochastic programming model, by addressing the demand- and supply uncertainties using discrete scenarios determines optimal strategic connections to minimize the strategic connection cost as well as the expected shortage cost at the habitats due to unmet demand. We present a small but realistic test case, conduct a sensitivity analysis to illustrate the underlying trade-offs among various components and highlight how the decision-maker can adjust system-flexibility by altering certain model parameters.
Keywords: Food insecurity; food waste; donor; beneficiary; strategic assignment; supply and demand uncertainty; stochastic programming; scenario; mixed-integer programming model; non-profit organization.
Efficiency Analysis of Selected Bank-Sponsored Mutual Fund Schemes in India
by RAJIB DEB, Soma Panja
Abstract: There has been growing literature related to performance analysis of the mutual fund (MF) industry concentrating on the non-parametric approach. Because of the practical and academic importance of mutual funds, it is becoming a vital area of research in finance. The present study seeks to gauge the efficiency of 40 equity mutual fund schemes that belong to seven asset management companies categorised as bank-sponsored under AMFI in India. The study uses data envelopment analysis technique as the prime tool for knowing the efficiency of selected schemes. The study discovers only seven schemes as efficient out of total sampled schemes and in which Canara Robeco Asset Management Co. Ltd offers the maximum number of efficient schemes as compared to others. The present study will offer direction for future research and will also provide individual investors with a guideline for selecting funds.
Keywords: bank-sponsored mutual funds; data envelopment analysis; performance efficiency.
Improved Memetic Programming algorithm
by Souhir Elleuch, Bassem Jarboui
Abstract: Automatic programming is an efficient technique that has contributed to an important development in the field of artificial intelligence. Genetic Programming (GP) is a well known automatic programming algorithm based on genetic algorithm and evolves programs. In the present paper, we propose a new automatic programming method called two-dimensional Memetic Programming. It combines GP with local searches. We also introduce a new program representation for automatic programming algorithms. For this reason, the Memetic programming algorithm is extended to evolve this program specific structure. To show the effectiveness of our method, we tested it on benchmark problems drawn from time series prediction and medical datasets classification, and we compared it with the related techniques.
Keywords: Automatic Programming; Memetic Programming; Local Search; Time-series forecasting; Classification.
Comparison of platoon formations using a departure time coordination heuristic
by Gajanand M. S, S. Sivanandham
Abstract: A platoon is a set of virtually linked vehicles that drive closely behind one another. Truck platooning is a fast-emerging application of connected and autonomous vehicles to help tackle the traditional problems of the transportation industry to reduce cost and minimise emissions. In this study, we present a departure time coordination based heuristic solution for platoon formations. We also use a comprehensive modal emission model to understand the influence of velocity and size of the platoon on fuel savings potential. We compare the heuristics performance on the different variants of the platooning problem in the literature with a central platoon coordinator and analyse the impact of the type of vehicle, speed, load and size of the platoon on the fuel savings potential of platooning. Numerical analysis shows a fuel savings potential of 6.4% to 8% for a platoon size of three with Heavy Duty Vehicles at 80kmph for different configurations.
Keywords: Platooning; Fuel Savings; Routing Problem; Departure Time; Platoon Formation; Freight Transportation.
Categorization of offshore wind production system
by Jon Lerche, Hasse Neve, Søren Wandahl, Allan Gross
Abstract: This paper investigates and describes the production system characteristics for offshore wind turbine assembly and compares it to manufacturing and construction. It requires understanding of the organizations, products and processes to categorize the production system for offshore wind farm assembly. This study compares explorative cases with literature describing the production system characteristics from production and manufacturing domains. The categorization is completed by comparing product-process first and then product-organization. To understand the identified differences, the results are displayed in matrixes with manufacturing and construction characteristics from the literature, compared with field notes, observations and archived data from wind turbine assembly cases. The results show offshore wind turbine assembly as a hybrid production system in this comparative study. The comparison contributes to the novel understanding of the wind industry and is theory building within operations research. It establishes a baseline for further operational research within the offshore wind domain.
Keywords: Construction; Comparison; Lean; Offshore Wind; Operations management; Production system theory.
Simulation-Based Optimization Approach to Multi-Choice Transportation Problem
by N.Tuba Y?lmaz Soydan, Ahmet Mete Çilingirtürk
Abstract: The classical transportation problem assumes that freight costs from source to destination are constant and that the supply and demand quantities are equal and strictly known, so the market for the product is well-balanced It thus involves a special type of linear integer programming, which becomes stochastic since the constraints or parameters are random variables from a known or unknown distribution Several studies have formulated well-known deterministic models under probabilistic restrictions The transformed models mostly keep the confidence level at a given minimum constant or else minimize the error level Also, there is a multi-choice stochastic transportation problem, which introduces several unit costs In this study, we try to simulate Roys (2014) multi-choice stochastic transport model with random supply and demand quantities from a given Weibull distribution and compare the results of distribution and total costs.
Keywords: Simulation-Based Optimization; Multi-Choice Transportation Problem; Weibull Distribution.
A Bibliometric and content analysis of core researches on Operations Research
by Nikunja Mohan Modak, Alok Raj, Shib Sana
Abstract: Operations research emerged as a discipline after the Second World War due to its efficiency to make better decisions. The socio-economic environment world over has changed over the last 50 years, and operations research has played a vital role in complex decision-making. Advanced analytical methods of operations research are effective for improving decision-making and solving real life problems in business, industry, and society. This work presents a bibliometric and content analysis of core publications of operations research. This study exclusively considers publications with operations research in their title. We have used SCOPUS, a reliable database, to collect relevant data. It presents overall publications and structure of citations. It comprehensively studies the significant contributions of journals, universities, and countries on this topic. Using the visualisation of similarities viewer software, it presents network visualisations and analyses co-occurrence of keywords, co-citations, and bibliographic coupling of institutions and countries. Finally, the paper reviews highly influential articles in this field and provides comprehensive direction for future research in this field.
Keywords: operations research; Scopus; bibliometrics; VOS viewer.
Cash discount associated permissible delay sensitive Economic Order Quantity (EOQ) systems in favor of deteriorating commodity of Weibull distribution receptive demand and Shortages
by Rakesh Tripathi, Hari Shyam Pandey
Abstract: Inflation is a major problem in the entire world. Inflation and time value of currency both are analogous to each other. In this learning demand is measured two Weibull parameters. Shortages and deterioration both are taken into account. Main goal of this work is to find the most favorable replenishment planning so that total cost in minimized. Mathematical models are consequential under the four dissimilar circumstances. Optimal solution is obtained by solution procedure. Numerical designs are offered to confirm the model expected in study. Sensitivity analysis is specified for distinction of dissimilar parameters. Mathematics 7.0 is used for finding numerical outcomes.
Keywords: Cash- discount; trade credits; Weibull distribution; deterioration; cycle time; Demand.
An Optimization and Simulation Hybrid Approach for Maternal Healthcare Facility Location-Allocation in the Indian Context
by Ankit Chouksey, A.K. Agrawal, Ajinkya N. Tanksale
Abstract: This paper addresses availability and accessibility issues related to maternal healthcare facilities, basic healthcare to neonatal services, prevailing in India. These issues are resolved on economic considerations in establishing and running healthcare facilities and the expenses on travel incurred by mothers-to-be (MTBs) in visiting them. This problem is formulated as a mixed-integer linear programming model for determining optimal number and locations of the healthcare facilities within the specified geographical boundary. The formulation also decides optimal allocation of MTBs to these centers that are available within a reasonable distance. Service demand of MTBs was considered to be deterministic. In reality, the demand, being random, may be high to cause healthcare service quality negatively. Hybrid optimization and simulation approach shows that the service quality deteriorates with the increase in demand variability or its mean value. This information is useful in deciding additional number of the service facilities to provide satisfactory service quality.
Keywords: Optimization and Simulation; Maternal healthcare; Facility location; Mixed-integer programming; Monte-Carlo simulation.
A Comparison of Different Mathematical Models for the Job Sequencing and Tool Switching Problem with non-identical Parallel Machines
by Dorothea Calmels
Abstract: This paper addresses the generalisation of the NP-hard job sequencing and tool switching problem with non-identical parallel machines and sequence-dependent setup times where a set of jobs is to be scheduled on unrelated parallel machines with machine-dependent processing and tool switching times. Three different mathematical models for two different objectives are presented and applied to newly generated test instances. The instances are compared and analysed using a commercial solver and an iterated local search heuristic. Overall, it is shown that the solution quality obtained by the mathematical models depends on the size of the problem instance as well as the tool requirements. The precedence-based formulation is superior in general to the position-based and time-index-based formulation for dense problem instances while the position-based formulation works well for sparse problems. With an increasing problem size, the metaheuristic requires significantly less time to find near-optimal solutions than the mathematical models.
Keywords: mixed integer programming; job sequencing and tool switching; tooling constraints; parallel machines; sequence-dependent setup times.
Replenishment Decision for Ameliorating Inventory with Time Dependent Demand and Partial Backlogging Rate
by Vijay Vir Singh, Yusuf Ibrahim Gwanda
Abstract: In contrast to deterioration, amelioration refers to a situation where stocked items incur increased value, quantity, or utility while in stock. It is generally seen in poultry, piggeries, wine industries, etc. when these items are kept on the farm or the sales counter, they usually incur increase in quantity and value. In this research, we study an inventory model that outlines the optimal replenishment decision for ameliorating items with a partially backlogged time-varying demand rate to raise productivity and understand opportunity cost due to lost sales. Until recently, most of the research in inventory has been focused essentially on deteriorating inventory, giving little or no attention to its ameliorative nature. Therefore, in this research, we developed an EOQ model for such items with time-dependent demand and partial backlogging rate. Using the differential calculus concept, the various Inventory optimizing functions, like total cost, number of replenishments, backlogging factors, etc. are computed.
Keywords: Ameliorating Inventory; Time dependent demand; Replenishment decision; Partial backlogging; Lost sales.
A multi-objective optimization model for production and transportation planning in a marine shrimp farming supply chain network
by Mr.Chaimongkol Limpianchob, Masahiro Sasabe, Shoji Kasahara
Abstract: The traditional operation of marine shrimp farming is widely practiced in Southeast Asia. Giant freshwater prawn farming is one of the main types of farming that also still operates traditionally. Many of these farms operate without advanced techniques for production planning, inventory control, and transportation strategic decisions throughout the supply chain network which are among the most important managerial activities in commercial farming. Maintaining product freshness is of vital importance for aquaculture product Therefore, this paper develops a multi-objective mixed-integer linear programming model for a marine shrimp farming supply chain network design problem. The problem is to plan production and control inventory according to constraints while maximize total profit surplus and minimize shortest route. A multi-echelon, multi-facility, and multi-period mathematical model is proposed such that real conditions are considered. In the end, some numerical illustrations are provided to show the proper Pareto solutions considering all of the objectives
Keywords: supply chain network; mixed-integer linear programming; marine shrimp farming; giant freshwater prawns; multi-objective optimization; production planning and inventory control; transportation planning.
Time Paradox in Transportation Problems
by Sonia, Subramanian Chidambaran
Abstract: The boom in E-commerce industry in recent years is reshaping delivery landscape and logistics needs to keep pace with this rapid e-commerce growth. One of the most important customer satisfaction KPIs in the e-commerce industry is to reduce the delivery time and is a key focus area for the market players.The present paper attempts to address this challenge by introducing the concept of a paradox in a time minimizing transportation problem (TMTP) which is a concave minimization problem. The paradoxical situations in cost minimizing transportation problems, fixed charge transportation problems, minimum cost flow problems and in many other variants of transportation problem have been extensively researched and well applied except for TMTPs. After defining the time paradox in a TMTP, we develop the condition of its existence. Further, a comparative study of paradox for a cost minimizing and time minimizing transportation problems has also been carried out.
Keywords: Time paradox; Time Minimizing Transportation Problem; Bottleneck Transportation Problem.
A Hybrid Tournament Differential Evolution Algorithm for Solving Optimization Problems and Applications
by Md Akhtar, Amalesh Kumar Manna, Avijit Duary, Asoke Kumar Bhunia
Abstract: The goal of this work is to propose a hybrid algorithm, combining Differential Evolution algorithm and Tournamenting process, for solving constrained and bound-constrained optimization problems. Considering different options of binary tournamenting, six variants of the proposed hybrid algorithm are developed. To test the efficiency and performance of the proposed hybrid algorithm, twelve benchmark optimization problems are considered and solved. From the obtained results of these benchmark problems, proposed six different variants of the hybrid algorithm are compared numerically as well as graphically. From these comparisons, the best variants of the hybrid algorithm for solving constrained and bound-constrained optimization problems are identified separately. Then by using these best variants, three well known engineering design problems are considered and solved. The computational results are compared with the results of some of the existing algorithms available in the literature. In each case, it is observed that the proposed algorithm performs well.
Keywords: Global Optimization; Constrained Optimization; Bound-constrained Optimization;Differential Evolution; Tournamenting.
A partial back-ordering inventory model for log-gamma degenerating items with quadratic demand and shortages
by K. Senbagam, M. Kokilamani
Abstract: The intention of this article is to explore; an inventory system for degenerated items includes quadratic demand and log-gamma degeneration rate. Degeneration is permitted on inventory which follows two-parameter log-gamma distributions. Stock out is permitted in the inventory system is completely and partially back-ordered. The cost of holding cost is assumed to be a constant. The aim of this economic order quantity pattern is to minimize the entire revenue of inventory optimization. The model can be used for businesses where the demand and rate of deterioration depend on time. Here we provide some numerical examples and sensitivity analysis are supported to demonstrate the solving methodology.
Keywords: The inventory system; degenerated items; Log-gamma degeneration; quadratic function; partial back-ordering; shortages.
Modeling and simulation of Bernoulli feedback queue with general customers' impatience under variant vacation policy
by Amina Bouchentouf, Mouloud Cherfaoui, Mohamed Boualem
Abstract: This article deals with a feedback queueing system with variant of a multiple vacation policy, balking, reneging, retention of reneged customers. On arrival a customer activates an impatience timer which is generally distributed. If a customer's service has not been completed before the customer's timer expires, the customer leaves the system. It is supposed that the impatience timer depends on the states of the server. The general distribution of impatience times as well as server's states-dependent reneging makes the analysis of the considered model difficult. We establish the equilibrium analysis of the queueing model, we derive its performance measures and examine it by a series of simulation experiments through a discrete-event simulation (EDS). This approach is appropriate for modeling such complex environment, it attempts to replicate the behavior of the system providing the system characteristic estimations.
Keywords: queueing; vacation; balking; reneging; general customers' impatience; discrete-event simulation.
Hybrid Multi-Objective Evolutionary (H-MOE) Algorithm for Solving RALB-II Problem
by Vigneshwar Pesaru, S. Venkataramanaiah, Mukund Nilakantan Janardhanan
Abstract: In this paper, we propose a mixed integer programming (MIP) model with dual focus on minimization of cycle time and total assembly line cost simultaneously. Due to NP-hard nature of RALB (Rubinovitz and Bukchin 1991), and also to avoid local minima in search space, a hybrid multi-objective evolutionary (H-MOE) algorithm developed based on the features of Non-dominated sorting Genetic Algorithm (NSGA-II) along with Simulated annealing (SA) local search algorithm and is used to solve the RALB-II problem. We conducted number of experiments using data sets selected from published literature (Mukund et al 2017b) and evaluated the performance of the proposed hybrid multi-objective evolutionary algorithm. From the experimental results, it is found that the proposed hybrid algorithm outperformed the algorithm proposed by Mukund et al (2017b) in five out of seven cases on saving in cycle time and four out of seven in terms of total cost saving.
Keywords: Hybrid Algorithm; Multi-objective; NSGA; Robotic Assembly Line; Parameter tuning.
Application of Multi-Objective Probabilistic Fractional Programming Problem in Production Planning
by Berhanu Belay, Srikumar Acharya, Rajashree Mishra
Abstract: This paper presents the application of multi-objective probabilistic fractional programming problem in production planning. The production planning model for a manufacturing company that produces multi-products with a specified period is formulated by considering some of the parameters in the right hand side of the constraints as random variables following continuous distribution namely gamma distribution. The formulated mathematical model is a multi-objective probabilistic fractional programming problem. In the solution procedure, the deterministic equivalent of the probabilistic programming problem has not been obtained. The analytical method for multi-objective fractional programming problem has also not been applied to solve the proposed model. A stochastic simulation based genetic algorithm is applied to solve the proposed model directly. A set of Pareto optimal solutions is obtained for the formulated production planning problem
Keywords: genetic algorithm;multi objective programming problem;probabilistic programming problem; stochastic simulation; fractional programming;production planning;gamma distribution;Pareto optimal solution.
Application and Technique of Inventory Control Theory in Pharmaceutical Sciences.
by Atma Nand
Abstract: The pharmaceutical inventory product management poses a unique problem in the hospitals and pharmacy shops. The inventory control theory plays a significant part in a pharmacological business. For every business, the simple and intuitive interpretation of all the available stocks is important. The determination of the importance of a pharmaceutical drug item should also consider other considerations, such as how severely its unavailability would affect patients. All the drugs are associated with an expiry date, so it is necessary to keep minimal safety stocks of pharmaceuticals products. In this article, we have been suitably classified all available pharmaceutical models and discussed in detail. This article is an overall review of most of the available pharmaceuticals Inventory literature.
Keywords: medicinal inventory; pharmacological inventory; inventory; perishable products; RFID technology.
A Demand and Supply Chain Inventory Management with Probabilistic and Time Dependent Price
by Nabendu Sen, Nabajyoti Bhattacharjee
Abstract: In real world, it has been a challenging part for the vendors and stockholders selling the perishable product. Especially, when price of the product reduces with time, due to high rate of deterioration and eventually vanishes. The products like vegetable scrap, food products, wood stock, etc. comes under this category. In this paper, we develop a demand and supply chain inventory model with deterioration and exponential demand to maximise the profit of a stockholder selling a perishable product. The selling price is probabilistic and a decreasing function of time so that, after a finite time limit the product has no market value. We consider three probability distributions uniform, triangular and gamma and compare the total profit under three distributions and represent the result graphically. We perform sensitivity analysis and interpret the result both theoretically and graphically. Further, we study the model under different situation and provide managerial implications.
Keywords: inventory modelling; probabilistic price; total cost; total revenue; total profit; optimisation.
Theoretical and Empirical Advances in the Assessment of Productive Efficiency since the introduction of DEA: A Bibliometric Analysis
by Thyago Celso C. Nepomuceno, Ana Paula C. S. Costa, Cinzia Daraio
Abstract: The field of productivity and efficiency analysis is growing exponentially, both in terms of new methods and approaches proposed to assess the efficiency of productive decision making units (DMUs), and in terms of innovative and traditional empirical application of existing methods. This survey provides a bibliometric investigation on the advances of the data envelopment analysis (DEA) from the seminal work of Charnes et al. (1978) to the most recent empirical and theoretical contributions. The most influential authors, outlets, contributions and frontier models are investigated through a timeline-based mapping and distance-based clusters of the state-of-the-art in the field of productivity and efficiency analysis with the support of the analytic tools CitNetExplorer and VOSviewer. The visualisation of the DEA relevant extensions is presented with the identification of application gaps and the evaluation of so far proposed methodologies based on a network of co-citations and bibliometric coupling. We provide a valuable reference for researchers to understand and overview potential advances in this field.
Keywords: heritage of Abraham Charnes; data envelopment analysis; DEA; frontier efficiency; scientific landscape; bibliometric network.
Stochastic Goal Programming and Metaheuristics for the Master Surgical Scheduling Problem
by Justin Britt, Xiangyong Li, Ahmed Azab, Mohammed Fazle Baki
Abstract: Planning and scheduling in a hospital require the consideration of several competing objectives, stakeholders, and resources. In this paper, methods for the master surgical scheduling problem (MSSP), which involves assigning surgeons to time blocks in operating rooms (ORs), are proposed. A stochastic weighted goal programming model (WGPM) with four goals and metaheuristics are used to perform elective surgery scheduling under uncertainty of both surgical durations and patient lengths of stay. In addition, discrete event simulation (DES) models and a decision support system (DSS) are developed. Computational experiments are used to evaluate the WGPM, validate the DES models, assess the relationships between the goals, and to tune and evaluate the metaheuristics. Results show that even though there are trade-offs between the goals that must be considered, it is possible to attain a high level of OR utilisation while meeting strategic targets and optimising recovery ward (RW) utilisation.
Keywords: operating room planning and scheduling; tactical planning; master surgical scheduling; decision support system; DSS; stochastic goal programming; discrete event simulation; DES.
Sensitivity in Efficiency and Super Efficiency Evaluation: Case of a Private Educational Institution
by Sandeep Kumar Mogha
Abstract: In this paper the performance of academic departments of a selected private institution is assessed for the academic year 2014 to 2015 using DEA-based dual CCR model. At the first stage, we use academic staff and non-academic staff as the input variables and total enrolled students, total pass students, students placed for jobs and research index as output variables. At the second stage, sensitivity analysis is used to assess the super efficiency and the ranking of the academic departments. The new slack model is also applied to measure the impact of slacks on evaluated efficiencies. The results suggest that four academic departments are technically efficient with an average efficiency score of 0.899 and the remaining three are inefficient and operating on increasing returns to scale. The super efficiency scores also suggest the outliers.
Keywords: dual CCR model; NSM model; sensitivity analysis; NorthCap University; NCU.
Informal-Contract farming in An Agriculture Supply Chain: A Game-Theoretic Analysis
by Shivshanker Singh Patel
Abstract: A contract in an agriculture supply-chain under market uncertainty leads to renege. Specially, when the contract enforcement cost is not very high it is prone to collapse. In this paper, a set of game theoretical models have been employed to analyse renege of the contract farming (informal-contract). To start with a normal form game-theoretic model with pure strategies has been utilised to model the price risk of the market and determine the outcomes for the players (firm and farmer); subsequently, a mixed strategy model has been studied. Owing to incomplete information under the informal-contract, a Bayesian Nash equilibrium and mixed strategy Bayesian Nash equilibrium have also been analysed. The results have been explained with an example of tomato contract farming of Southern India. From the business standpoint the results and renegotiation framework presented in this paper can be utilised to avoid a renege and dispute in the contract farming.
Keywords: contract farming; informal contract; supply chain; Bayesian Nash equilibrium; re-negotiation.
An efficient approach for the Petrol Station Replenishment Problem: An Algerian case study
by Besma ZEDDAM, Faycal Belkaid, Mohammed BENNEKROUF
Abstract: In a logistic process, the goods distribution is an important task. It is also a critical activity that needs to be optimised according to company policy. the petrol station replenishment problem (PSRP) is one of the transportation problems concerned with replenishing a set of fuel stations with the different petroleum products. This problem presents a particular case of the multi-compartment vehicle routing problem (MC-VPR). In this paper, a new bi-objective approach is proposed in order to treat the PSRP. A novel MILP model is proposed based on a real life case study (the Algerian company of fuel distribution NAFTAL). Two objectives are considered: gain maximisation and carbon emissions minimisation. The economic objective is optimised independently of the environmental one, then they are joined by adapting a multi-objective method LP-metric. Finally, computational results are presented in order to show the efficiency of our green approach for a sustainable transportation system.
Keywords: petrol station replenishment problem; PSRP; multi compartment; carbon emissions; bi-objective; LP-metric.
The Kalos Balanced: a novel integrated performance assessment and improvement method
by Seyed Mostafa Bahadornia, Seyed Mohammad Khalili
Abstract: These days, managers are surrounded by the extensive spectrum of decision-making environments which are more acute both in quantity and quality. Consequently, it is necessary to utilise expert multiple attribute decision-making methods which are fit to the mentioned environment. To achieve this goal, a novel balanced multiple criteria improvement method, Kalos balanced has been proposed in this article which not only evaluates candidates but also provides a mathematical model for improving the desired candidate. Despite the traditional weight multiplication methods, a novel smooth weighing function has been offered in this study which leads to moderate assessment and balanced improvement based on mathematical proofs. Finally, an example has been assessed and improved based on the mentioned system.
Keywords: multiple attribute decision making; performance assessment; performance improvement.
New class of optimal multiple stopping times problems
by Noureddine Jilani Ben Naouara, Faouzi Trabelsi
Abstract: This paper is devoted to study a new discounted nonlinear optimal multiple stopping times problem with discounted factor ? > 0 and infinite horizon. Under the rightcontinuity of the underlying process, we show that the problem can be reduced to a sequence of ordinary optimal stopping problems. Next in the Markovian case, we characterise the value function of the problem in terms of ?-excessive functions. Finally, in the special case of a diffusion process, we give explicit expressions for the value function of the problem as well as the optimal stopping strategy. As explicit example in finance, we apply our theoretical results to manage a new generalised swing contract which gives its holder n rights to mark the price X of a stock, where the payment is only allowed at the final exercise time rather than at each exercise time as in the classical swing contact.
Keywords: optimal multiple stopping; discounted factor; Markov process; diffusion process; Snell envelope; dynamic programming; ?-excessive functions; swing option; COVID-19 pandemic.
Factors affecting suppliers capacity in outsourcing: a study of the Water and Wastewater Company of Iran
by Hadi Sarvari, Masoud Raeisi Dehkordi, Matteo Cristofaro, Daniel W. M. Chan, Nerija Banaitien?
Abstract: What are the major factors able to increase the capacity of suppliers in outsourcing processes? To answer this research question, a three-round Delphi survey was administered to an expert panel composed of 50 industrial experts of the water and wastewater company (WWC) in Iran. The administered questionnaire
Keywords: water industry; wastewater industry; outsourcing; Delphi; supplier capacity; Iran.
Hybridized Ant Colony Optimization for the Multi-depot Multi-compartment capacitated arc routing problem
by Ali Kansou, Bilal Kanso, Adnan Yassine
Abstract: This paper considers the multi-depot multi-compartment capacitated arc routing problem. It consists to find a set of vehicle routes with minimal travelled distance that satisfy the demands of a set of customers for several products. This problem has some important applications such as in the fields of transportation, distribution and logistics since companies are increasingly using multiple depots to store their products and separate compartments which are necessary since each product has its own specific characteristics and cannot be mixed during transportation. In this paper, a new approach based on the ant colony optimisation that is hybridised with a simulated annealing algorithm is developed. Computational experiments are performed on a benchmark of instances taken from the literature, and a set of real-life instances, and on another new set of random large-scale instances. The proposed metaheuristic generates high-quality solutions compared to the existing algorithms and particularly the results on the new instances seem promising, purposeful and powerful.
Keywords: metaheuristic; arc routing problem; multi-depot; multi-compartment; ant colony optimisation; ACO; simulated annealing algorithm.
Empirical Analysis of Employees Commitment, Organizational fitness Elements and Intention-to-Stay in the Malaysian Construction Companies: Mediating Influence of Organizational Commitment
by Taofeeq Durojaye Moshood, Gusman Nawanir, Fatimah Mahmud
Abstract: A concept that is commonly adopted in corporate settings is employee-intention-to-stay. At the same time, a variety of studies have been conducted on this same concept. While a large number of studies relating to management approaches have concentrated on employees motivation, very few studies have been undertaken concerning employees intention to remain in their various companies. Because it is a very significant criterion in deciding a workers stay in the company, this study, therefore, intends to explore the connection between fit organisation elements and staffs intention to remain in the construction industry, with the organisational commitments as a mediating variable. Also, the approach was structured to concentrate on the studys issues and objectives through quantitative analysis design using a positivist research paradigm. The findings showed a direct correlation between organisational fit elements and the workers intention-to-stay in their various companies. Organisational commitment fully mediates the relationship that fits the organisations elements had with the intention-to-stay. Findings suggest that the three components of organisational commitment, as well as workers intention-to-stay, have a high possibility of making employees to stay in their various organisations.
Keywords: intention-to-stay; fit organisation; organisational commitment; construction industry; PLS-SEM.
Absolute and Relative Weight Restrictions in DEA - An Comparison
by Gerald Fugger
Abstract: In most data envelopment analysis (DEA) models, the decision maker (DM) only selects inputs and outputs and does not have to make any previous assumptions about the underlying production process. Without additional weight restrictions, the linear program may assign zero weights to inputs and outputs of certain decision-making units (DMUs). Specialised DMUs can be calculated as efficient because only subsets of the data are included in their efficiency calculation. In most cases, however, it is not desirable to ignore inputs or outputs previously selected by the DM, so technical efficiency can overestimate true efficiency. Additional weight restrictions can avoid specialised DMUs, further improve discrimination between DMUs, and allow the implementation of prior knowledge of the production process. This publication provides a comprehensive literature review of relevant studies on additional weight restrictions in the DEA and discusses their implementation and effects. The latter aspects are demonstrated first for five artificial DMUs and then for 1,000,000 simulated DMUs.
Keywords: data envelopment analysis; DEA; weight restrictions; assurance regions.
Algorithm for Automation of the Teacher-Course Allotment
by Sanjeev Kumar, Rakesh Pandey, R.P. Mohanty
Abstract: The university course timetabling problem (UCTP) is one of the important scheduling problem, which is a NP-hard category problem. The teacher-course allotment is a sub-problem in this category. It is a time-consuming and complicated exercise in academic institutions and influences the quality of teaching due to subjectivity in allocation decision. This problem is solved manually by holding a number of meetings at institute level and even after such involved interactions, there is no guarantee that courses are allocated in a correct fashion in order to meet program and course objectives as well as for the satisfaction of all stakeholders. To overcome this subjective practice, it is proposed to develop and validate an algorithm to automate this tedious job. The proposed algorithm consists of two phases. In Phase-I, a bipartite graph is used to obtain the teacher-course preferences-based initial solution of the problem, and then conflict free final solution of teacher-course allocation is achieved in Phase-II. To validate, a software application with rich graphic user interface (GUI) is also developed and tested on an Indian university dataset. The results have been implemented with a good degree of stakeholders satisfaction.
Keywords: university course timetabling; teacher-course allotment; bipartite graph; NP-hard; algorithms; scheduling; teaching-learning process.
A Classical Retrial Queueing Inventory System with Two Component Demand Rate
by M. Abdul Reiyas, Kathirvel Jeganathan
Abstract: We deal a two component demand rate inventory system that composed of two arrival patterns of customers called as homogeneous and non-homogeneous arrival patterns. The homogeneous arrival pattern occurs at zero inventory and the arriving customer compulsorily enters into an infinite orbit. But at the time of positive inventory, the non-homogeneous arrival pattern occurs at a rate which depends on the present stock level (PSL). We set a classical retrial policy (CRP) for an orbital demand and (s, Q) ordering policy to fix for any reorder. In this model, Laplace-Stieltjes transform (LST) is used to investigate the waiting time of a retrial demand under the stability condition and all the necessary system characteristics are measured under matrix-geometric approach and further the sufficient numerical tabulations and illustrations are detailed to explore the goodness of the proposed model.
Keywords: stock-dependent; retrial queue; waiting time; lead time.
Evaluation of enablers of supply chain resilience and responsibility in India during large-scale disruptions: An ISM-ANP approach
by Rohit Sindhwani, Venkataramanaiah Saddikuti, Omkarprasad S. Vaidya
Abstract: The healthcare and economic distress caused by large-scale disruptive events is most severe. The recent pandemic, SARS-CoV-2, has affected the entire world with its relentless energy. Only few supply chains (SCs) have remained resilient during disruptions. We highlight that these organisations do not just focus on SC resilience; the innate nature of being responsible has helped them stay afloat. Thus, we understand and identify various enablers of resilient and responsible SCs for survival during large-scale disruptions in India. 15 enablers and 30 sub-enablers for SC survivability are identified from literature and verified by experts. Integrated ISM-ANP approach and MICMAC analysis is adopted to develop a conceptual framework and prioritise enablers for SC survivability. The three most important sub-enablers in near term are advanced tracking and tracing system (0.0807), information sharing of business objectives (0.0776) and multi-way partnership (0.0776), respectively.
Keywords: survivability; responsible supply chain; supply chain resilience; pandemic disruption; SARS-CoV-2; ISM-ANP; India.
An optimal pricing and quality assessment model for consumer returns in a multi-period closed-loop supply chain
by Kamil Ciftci, Yertai Tanai, George R. Wilson
Abstract: We propose a framework for a single demand and its returns occurring in a multi-period setting. The goal of this study is to determine price and processing quantities of returns for a retailer when she is faced with stochastic returns and numerous quality conditions for returns specific to a particular period. We formulate the expected profit function of a single demand and its returns over the sales periods and analytically derive the optimum price expression. Furthermore, we develop an extensive numerical experiment to analyse the effect of key parameters on the profit and price. The research herein shows that an increasing number of quality categories for returns improves the total profit significantly over the sales periods. Likewise, we find that the number of quality categories for returns can also affect changes in the price indicating the importance of sensitivity of the retail price to the returns quality.
Keywords: closed-loop supply chain; returns quality; consumer returns management; multi-period planning; pricing decisions.
Portfolio Optimization in Emerging Markets: Mean and Median Models Assessment
by Mai Ibrahim, Mohammed El-Beltagy, Motaz Khorshid
Abstract: Portfolio optimisation is instrumental in financial decision making. The basic Markowitz model is considered a milestone in financial theory but many examples including emerging markets were shown not to follow Markowitzs assumption of normality, hence alternative models have been suggested. The traditional mathematical programming that suits well the Markowitz model falls short in other complex situations of alternative portfolio models. Multi-objective evolutionary algorithms are well suited to solve these models with conflicting objectives regardless of their complexity and mathematical nature. Four models that belong to the mean models are compared to three median models and are formulated as multi-objective problems and solved using the non-dominated sorting genetic algorithm-II. The models are tested on real data of the Egyptian index and compared to two other emerging markets. The results show the outperformance of the median models over the mean models and the tail risk measures over the symmetric risk measures.
Keywords: evolutionary computations; multi-objective programming; conditional value at risk; CVaR; value at risk; VaR; mean models; median models.
Multi-item EOQ model for deteriorating items having multivariate dependent demand with variable holding cost and trade credit
by Dharmendra Yadav, S.R. Pundir, Manisha Sarin
Abstract: In the present study, a multi-item EOQ inventory model for deteriorating items is explored by considering customers demand as a function of stock and selling price. Further, holding cost is considered as the function of stock-level and shortages are allowed, which partially backlogged. Further, trade credit policy is one of the attractive policies adopted by the supplier in the competitive market to boost the demand. Two different inventory models are investigated by considering the two situations, namely: a) the end stock level is negative; b) the end stock level is positive or zero. Different lemmas and theorems are provided to develop the search algorithm to obtain the optimal solution. The study shows the importance of multivariate demand and trade credit of the optimal policy of inventory. The feasibility of the proposed model is analysed with the help of a numerical example. Sensitivity is also carried out for critical parameters.
Keywords: Multi-Item; Multi-variate Demand; Variable Holding Cost; Partial Backlogging; Trade Credit.
Comparative Analysis between Serial Systems with Cold Standby Units
by Ibrahim Yusuf, Humairah Baballe Ilah
Abstract: This paper studied reliability assessment of three dissimilar systems configured as series-parallel systems. Three probabilistic models are discussed. Each system consists of six units. It is supposed that the failure and repair time of all components are considered to be exponentially distributed. Using linear differential-difference equations, mathematical models for the steady state availability and mean time to failure are derived, examined and compared for each system. Through numerical examples, the systems are compared and ranked to determine the optimal system.
Keywords: reliability; cost-benefit; serial; cold standby; performance.
Selection of Materials Formulation for Non-Asbestos Friction Materials using Entropy Weight Based-TOPSIS & COPRAS Multi-Criteria Decision Making
by Neet Vadgaonkar, Tejas Fulwala, Saurav Mahajani, Dinesh Shinde
Abstract: Friction materials are the prime materials which should have higher as well as stable coefficient of friction and lower wear at various braking applications. The demand of these diverse tribological characteristics makes the selection of materials formulation for the friction materials, a critical task. This paper presents an attempt to select the materials formulation for the friction material using two advanced MCDM methods (TOPSIS and COPRAS). Friction materials were prepared at one of the manufacturer from three materials formulation under study (FM01, FM02 and FM03). The experimental set up was developed dedicated to the testing of the friction materials at actual operating conditions. Based on the experimental results, seven criterions were chosen for assessment of the materials formulation in the MCDM approach. TOPSIS and COPRAS methodologies have systematically implemented for evaluation of the materials formulations. Based on the assessments it was concluded that the current approach is useful in evaluation of materials formulation based on the experimental performance. The formulation FM03 was found as a best material formulation among three.
Keywords: friction materials; materials formulation; Taguchi method; multi-criteria decision making; MCDM; TOPSIS; COPRAS.
A study on optimization of vehicle allocation for evacuation during a site emergency at a nuclear power plant
by Anirudh Chandra, Murali Seshadri, Probal Chaudhury
Abstract: Indian nuclear power plants have graded engineered safety features because of which accidents with large scale consequences are highly improbable. However, regulatory requirements state the necessity of a site evacuation following a site emergency or an off-site emergency. Planning for this emergency requires allocation of evacuating vehicles. This study provides a simplified model of evacuation, with focus on minimising the travel time. The vehicle allocation was considered to be an optimisation problem. Mixed integer linear programming (MILP) was used to solve this constrained optimisation problem for a particular nuclear facility site. Different evacuation modes were formulated and the evacuation travel times for each mode was estimated. The most reasonable mode of evacuation was found to be a simultaneous supply of vehicles from vehicle depot to facilities, followed by a sequential evacuation of each facility to the exit. This solution reduces unnecessary congestion at exits and also reduces the travel time.
Keywords: site emergency; evacuation; mixed integer linear programming; MILP; optimisation; emergency response management; nuclear emergency.
Correlation coefficients in T-spherical fuzzy environment using statistical viewpoint and their applications
by Dinesh K. Sharma, Surender Singh, Abdul Ganie
Abstract: A T-spherical fuzzy set (T-SFS) is a generalisation of spherical fuzzy sets (SFSs), picture fuzzy sets (SFSs), intuitionistic fuzzy sets (IFSs), and fuzzy sets (FSs) in which the sum of the qth power of membership, the qth power of non-membership and qth power of neutrality values is at most one. The correlation coefficient is a crucial tool in fuzzy/non-standard fuzzy theory and has been applied in various fields such as clustering, pattern recognition, medical diagnosis, decision-making, etc. However, the existing correlation coefficients for T-SFSs give only the degree of correlation between two T-SFSs but do not tell us the nature of correlation (negative or positive). In this study, we propose two correlation coefficients for T-SFSs, which not only give the strength of correlation between two T-SFSs but also tell us whether the two T-SFSs are positively correlated or negatively correlated. We also discuss several properties of these correlation coefficients. We apply these correlation coefficients to solve a pattern recognition problem in the T-spherical fuzzy environment and compare the results with some existing measures. Further, by considering linguistic hedges, we theoretically and empirically contrast the performance of the proposed coefficients of correlation for T-SFSs with several existing measures.
Keywords: correlation coefficient; picture fuzzy set; PIFS; linguistic hedges; spherical fuzzy set; pattern recognition; T-spherical fuzzy set; T-SFS.
Stochastic closed-loop supply chain models: literature review, recent developments, and future research directions
by Omar Mohamed Omar Elfarouk, Kuan Yew Wong, Shamraiz Ahmad
Abstract: A closed-loop supply chain (CLSC) has been defined as a path that the material flows, starting from suppliers till it arrives at customers as a final product, including product recovery from customers to manufacturers for various usages. A stochastic CLSC handles uncertainty in critical parameters that affect CLSC design. This novel study presents a stochastic CLSC review and categorises uncertainty types applied to stochastic parameters under analysis. Also, the study describes various algorithms that are suitable for solving the different stochastic CLSC models. The research benefits practitioners and researchers by creating guidelines for stochastic CLSC design and discusses the strengths and weaknesses of algorithms used. The results showed the significance of a hybrid genetic, particle swarm optimisation (hybrid GA-PSO) in optimising constrained stochastic CLSC models and the advancement of stochastic CLSC research in the automotive industry. Future research should explore more uncertain parameters, methods of modelling social aspects, and new strategies to implement in stochastic CLSC.
Keywords: closed-loop supply chain; CLSC; stochastic CLSC; solution algorithms; modelling techniques; uncertainty types; uncertainty parameters; reverse logistics; hybrid particle swarm optimisation.
A modified presidential election algorithm for optimal tuning of proportional
by Hojjat Emami
Abstract: This paper uses a socio-politically inspired meta-heuristic algorithm based on the behaviour of voters and candidates named modified presidential election algorithm (PEA-II) for proportional-integral-derivative (PID) controller design. The incentive mechanism of PEA-II is enhancing the knowledge sharing and search capability of the canonical presidential election algorithm (PEA) by introducing a new positive advertisement and migration operator. By the new positive advertisement, PEA-II employs the best local and global knowledge of the agents to conduct the searching process in the solution space. The migration operator maintains diversity in the population and keeps the algorithm away from converging too fast before exploring the entire solution space. The proposed approach is evaluated using three well-known PID controller plants. The results show the superiority of the proposed algorithm in comparison with other counterparts.
Keywords: engineering optimisation problem; control; PID tuning; modified presidential election algorithm; PEA-II.
Performance of some discriminant analysis techniques
by Michael O. Olusola, Sidney I. Onyeagu
Abstract: This paper re-appraises the use of the minimised sum of deviations by proportion method (MSDP), the linear discriminant analysis (LDA) embodied in Minitab and the logit discriminant analysis (LoDA), for allocating observations into one of two mutually exclusive groups using some examples. In a recent paper, the MSDP was proposed as a means of generating a discriminant function that separates observations in a training sample (or development sample) of known group membership into specified groups. In the MSDP formulation, the sum of the proportion of exterior deviations is minimised subject to the group separation constraints, the normalisation constraint, the upper bound constraints on proportions of exterior deviations and the sign unrestriction vis a vis the non-negativity constraints. The decision rule on group-membership prediction is constructed using the apparent error rate. This study compares the performance of the MSDP with the LDA and LoDA based on their classification accuracy. The obtained results indicate that the LoDA is not suitable for the examples considered and that the MSDP is an appropriate alternative to the LDA.
Keywords: binary classification; hit rate; linear discriminant function; linear programming; minimised sum of deviation by proportion method.
Data Envelopment Analysis in Efficiency Measuring of District Central Cooperative Banks in India: a case study
by Mohd Shamim Ansari, Monika, Irfan Ali
Abstract: Over time, cooperative banks lost their dominance in agricultural credit which they enjoyed earlier, and presently they are facing many issues such as deposit management, liquidity management, deterioration in asset quality and so on which affect the performance and efficiency of banks. This study will help the policymakers and management to understand the nature and extent of inefficiency in District Central Cooperative Banks (DCCBs). Efficiency is essential for profitable growth of any decision-making units (DMUs), which will ensure value appreciation and survival in the long run. This paper is an attempt to measure the technical efficiency of DCCBs of Uttar Pradesh by applying Charnes, Cooper and Rhodes (CCR) model (Charnes et al., 1978) of data envelopment analysis. For the study purpose, all the 50 DCCBs operating in the Uttar Pradesh state of India has divided into 18 divisions as per the zonal classification of Uttar Pradesh administration. The estimated result shows that two-division are relatively most efficient, while three-division are less efficient. By improving the management of NPA, deposit management, increasing borrowing, loans and advances, less efficient banks can improve their efficiency.
Keywords: ooperative; non-performing asset; NPA; technical efficiency; Charnes; Cooper and Rhodes; CCR model; data envelopment analysis; DEA.
Inventory Policy Determination in MSMEs using Intuitionistic Fuzzy Sets based on Learning Aided Decision Support System
by Mahuya Deb, Kandarpa Kumar Sarma
Abstract: The successful operation of micro, small and medium enterprises (MSME) requires an effective supply chain linking manufacturers and distributors so as to minimise cost, reinvent channel models, and optimise collaborative relationships. In order to overcome the uncertainty present in this chain, inventory management policies are adopted which are crucial for enhancing, smooth production plans, and lower operation costs. Intuitionistic fuzzy (IF) set is considered to be an appropriate tool to model uncertainty in the chain. This paper deals with inventory policies regulated by IFS which would be applicable to the MSMEs. Normalised Euclidean distance method is used to measure the difference between each enterprise and each inventory policy respectively so as to select the best set of inventory management policy suitable for a unit. Further, the work involves the design of a decision support system (DSS) based on learning aided technique which provides an automated approach to the work.
Keywords: micro; small and medium enterprise; MSME; inventory policy; decision support system; DSS; Euclidean distance; triangular intuitionistic fuzzy number; TIFN.
How to Bring Manufacturing Back?
by Ziping Wang, Huafan Ma
Abstract: Moving manufacturing back to the US has been in many fierce debates. While many believe that reshoring is beneficial to the US through creating more jobs, our paper intends to gain more insights into this issue by studying a sourcing game between global firms and governments. Global firms may choose between offshoring and reshoring. Governments, as tax policy makers, aim at improving social welfare. First, our analysis indicates that firms may choose reshoring even if there are cost advantages to offshoring. Secondly, while reshoring may increase employment in the US, it may also have a negative effect on the overall social welfare. Thirdly, when the labour cost in the US is moderately higher, the government may launch new tax policies to motivate reshoring and improve social welfare. Finally, numerical examples demonstrate that reshoring improves social welfare in labour-intensive industry, while tax policies may curb such improvement with high tax rates.
Keywords: reshoring; supply chain management; tax policy; social welfare; production function.
A Nonlinear Goal Programming Approach with a Modified Search Algorithm to Achieve Student Outcomes in College Education
by Murat Cal, Sibel Atan
Abstract: We introduce a modified search algorithm to solve a nonlinear goal programming model to achieve multiple goals to the highest extent while minimising the total deviation from these targeted goals. We develop our model in an education environment that implements gamification in teaching hours, and learning outcomes are evaluated by assessments. Our parameters are then evaluated through experimental analysis and we provide insights on their accuracy. It is shown that our algorithm finds solutions within 1 to 10 per cent of the optimal solutions for different intervals, and these solutions are found instantaneously. Our model answers how much time of a teaching hour should be allocated for gamified elements, and how a game-based environment can be established together with an evaluation system. The study in that sense is unique as it combines a nonlinear goal programming model with gamification in teaching and it provides a framework to evaluate student outcomes to cope with educational objectives.
Keywords: nonlinear goal programming; heuristic algorithms; education theory; optimisation.
INVENTORY MODEL FOR THE GROWING ITEMS WITH PRICE DEPENDENT DEMAND, MORTALITY AND DETERIORATION
by Amit Kumar Saraswat, Ashish Sharma
Abstract: Growing items like live stocks, chicks, etc. gain weight in the growing phase but some of them are lost due to mortality. In the selling phase, some inventory lost due to deterioration. Such aspects make procurement decision quite difficult for these items. In the light of such aspects, we developed an inventory model for the growing items with price dependent demand, mortality and deterioration. Shortages are partially backlogged. Our aim is to optimise the total cost by determining the optimal ordered quantity and total cycle length. Convexity of the cost function with respect to the decision variables has been discussed analytically. Solution procedure along with numerical example at different percentage of backlogged quantity is provided to show the applicability and validity of our model. Sensitivity analysis shows that total cycle length is the most sensitive among all the decision variables and parameters.
Keywords: growing items; price dependent demand; deterioration; mortality; inventory model.
Optimal Warehouse Location and Size In Practice
by Richard Caron, Tareq Oshan
Abstract: Facility location decisions are crucial in supply chain network design because they affect a firms profitability and success. We present an example of the optimal selection of the location and size of warehouses for a Canadian company with operations across the nation. We begin with a description of the optimisation model that will be used to determine the size and location of new warehouses as well as the allocation of branches to warehouse. We will then discuss the characteristics of the company and explain the challenges that were overcome in fitting the application to the model. We continue with an analysis of the solutions and follow that with a summary of lessons learned.
Keywords: supply chain network design; application; case study.
Joint inventory, promotion and preservation decisions for deteriorating items with maximum lifetime and stochastic demand under two-level partial trade credit
by Hardik Soni, Ashaba Chauhan
Abstract: This study models a joint inventory, promotional effort and preservation decision-making problem for deteriorating items with maximum lifetime under a two-level partial trade credit and allowable shortages. This paper considers a supplier-retailer-customer supply chain model which allows: 1) for settling the cost of purchasing, the supplier offers a partial trade credit to the retailer and at the same time retailer offers a partial trade credit to the customer; 2) the upstream(supplier-retailer) credit period increases sales of the supplier and revenue of the retailer, the downstream (retailer-customer) credit period not only lifts demand but also the opportunity cost; 3) the deteriorating product not only deteriorate continuously but also it have maximum lifetime and to reduce the deterioration rate we use the preservation technology; 4) price and promotional effort dependent random demand; 5) shortages are considered. The objective is to find the optimal promotional effort, preservation technology investment, length of time for the inventory level reaches zero and replenishment cycle strategies while maximising the total profit per unit time. Numerical examples are included to illustrate the algorithmic procedure and the effect of key parameters is studied to analyse the behaviour of the model.
Keywords: inventory; deterioration; preservation technology; promotion; maximum lifetime; partial trade credit; supply chain.
De-i-fuzzification of Linear Interval-Valued Intuitionistic Fuzzy Number, and its Application in Operation Research Arena
by Sankar Prasad Mondal, Avishek Chakraborty, Shilpi Pal, Shariful Alam
Abstract: In this article, we have envisaged the linear interval valued intuitionistic fuzzy number (IVIFN) from various viewpoints. We have introduced the technique of ranking by using the concept of distance measure of linear interval valued intuitionistic fuzzy number. Additionally, the concept of de-i-fuzzification is introduced here using two disjunctive logical approaches and its result is explained in this article which will help us converting a linear interval valued intuitionistic fuzzy number into a crisp number. Lastly, the validation of the model is observed by using two different real life problems firstly, in inventory control and secondly, in transportation arena. The paper suggests two different methods of de-intuitification in linear interval valued intuitionistic fuzzy domain and the comparison between the two methods by using a suitable algorithm has been observed in above real life scenarios that connects all invented results.
Keywords: inear IVIFN; ranking; distance measure; de-i-fuzzification; inventory control; transportation problem.
Statistical distribution and analysis of secondary queue of railway passengers
by S.M. QASIM, Jamal Ahmad Farooqui
Abstract: Millions of passengers commute through trains in India every day. Still, thousands of waitlisted tickets are cancelled due to the non-availability of accommodation in the desired train on a particular day. Such cancellations result in dissatisfaction and discomfort to the waitlisted ticket holders and loss of business to Indian Railways. The queue of waitlisted ticket holders, called secondary queue, form when the berths in demand are less than the number of berths available in the desired class of accommodation in a particular train on a specific date. The small number of passengers from this queue are served with confirmed tickets surrendered by the passenger from the primary queue holding confirmed tickets. This paper, a portion of a larger study, attempts to identify the statistical distribution of arrivals and service for the secondary queue. Stationarity and interdependence have been examined for inter-arrival time and service time in context of sleeper (SL) class accommodation of Vaishali superfast express train. This has been found the secondary queue of Indian Railways advanced reservation passenger system follows G/G/C/K model of queuing theory. The results are expected to help the Indian Railways determine various queue parameters and hence optimise the system.
Keywords: railway reservation; primary queue; secondary queue; statistical distribution; stationarity.
ORDER PICKING AND STORAGE OPTIMIZATION IN A WAREHOUSE USING AGENT BASED MODELING
by P. Raghuram, Anuj.S Jain, Souryadeep Mazumder
Abstract: Warehouse management is an integral part of the supply chain and optimisation of warehouse operations can minimise redundant movements of pickers and can reduce processing time, thereby maximising the profits. In this paper, our objective is to develop a simulation model to find the optimal number of forklifts and arrival rate of goods by considering various factors like distance travelled by pickers, picker utilisation, storage and retrieval times. The warehouse layout is found through the number of racks, number of vertical levels and aisle width using genetic algorithm in MATLAB. The objective function is to minimise the total operational costs considering space and arrival constraints. The warehouse design parameters after optimisation are used in the simulation model to develop a new layout. The number of pickers and arrival rate of goods is obtained, analysed and compared. It is observed that further reduction in the aforementioned factors are obtained.
Keywords: warehouse optimisation; order picking; storage; handling; agent-based modelling; genetic algorithms.
An Optimization Approach in Trough Angle Selection of Conveyor Five Roll
by Theerasak Srimitrungroj, Tarit Rattanamanee
Abstract: This paper study the optimisation techniques by using numerical method for analysing selection problems, choosing the size, length and angle of inclination for the conveyor belt roller of conveyor five rolls to obtain the maximum material transfer rate. The mathematical model is formulated as nonlinear programming. The Lagrange multiplier technique is used to solve the solution. The numerical result shows that setting trough set angle number two (?2) twice as trough set angle number one (?1) yields the maximum material transfer rate.
Keywords: trough angle selection; belt conveyor; bulk material handling; optimisation.
Distribution of occupied resources on a fractional resource sharing in a queueing system
by Toky RAVALIMINOARIMALALASON, Mirisoa RAKOTOMALALA, Falimanana RANDIMBINDRAINIBE
Abstract: Many server systems can share their resources by fractional way not discrete. It can be found in major cases of communication systems sharing power, spectrum or bandwidth resources for example. The objective of this work is to build analytical expressions of the amount of occupied resources in a structure modelled as queueing system. The queue server shares its resources to customers that request services to him. Both infinite and finite capacity are highlighted and the requested resources can be fractional. The amount of occupied resources as real-valued random variable is characterised by its distribution functions that we proposed in this paper. They are validated by simulations, and then can be used to predict the performances of such system or to dimension the appropriate needed capacity. Impacts of system load factor and system capacity has been also analysed.
Keywords: queueing; dimensioning; load factor; resource occupation; resource sharing.
Operational Performance Evaluation & Efficiency Assessment of Thermal Power Sectors of Pakistan Using Data Envelopment Analysis
by Sadam Hussain, Faheemullah Shaikh, Laveet Kumar, Zulifqar Ali
Abstract: Energy is a life-line for almost all human activities and progress. Retrospective analysis of the increase in energy demand shows that meeting future energy requirements would be one of the severe problems to sustain the socio-economic activities in the world. The aims and objective of this study is to evaluate the power generation capacity of different thermal power plant in Pakistan using data envelopment analysis (DEA). Performance comparison includes refined furnace oil versus natural gas versus dual fuel versus coal and also GENCOs versus IPPs versus K-Electric power plants. Finding from the results indicates that natural gas outperformed as compared with refined furnace oil-based power plants dual fuel-based, coal-based thermal power plants. Results show that the performance of IPPs is high in comparison to KElectric and GENCOs. Accordingly, based on these results several policy implications have been planned to increase the performance of available thermal power sector in Pakistan.
Keywords: operational performance; efficiency assessment; data envelopment analysis; thermal power plants; Pakistan.
Using Constructivist Multi Criteria Decision Aid to Evaluate the Workforce Sizing in Public Organizations: The case of a Brazilian University
by Juliana Flores, Andre Longaray, Leonardo Ensslin, ADEMAR DUTRA, Sandra Ensslin, Vilmar Tondolo
Abstract: When addressing staff sizing management, the workforce that is required to meet the institutions objectives must be quantitatively and qualitatively identified and analysed, taking the institutions environment into account. Most studies concerning workforce sizing in learning institutions are limited to measuring faculty performance. Therefore, a gap in the literature exists concerning a performance evaluation of the sizing procedures for the administrative workforce at universities. We developed model to determine the requirements for a workforce sizing at a Brazilian public university. The research was classified as applied, exploratory, and descriptive, and it was divided into qualitative and quantitative steps. Utilising a constructivist multicriteria decision aid approach, 83 primary evaluation elements and 119 descriptors were identified. The status quo analysis revealed three areas with performance levels significantly lower and 50 indicators that are at a compromising level, for which action plans were proposed. The built model supported the manager in the performance evaluation of the staff sizing procedures.
Keywords: performance evaluation; MCDA-C; staff sizing; universities; human resources.
A separable programming approach for resource optimization in controlling epidemics
by Anuradha Mahasinghe, Sanjeewa Perera, Hasitha Erandi
Abstract: Optimal resource allocation in controlling epidemics is a topic of importance, in particular to health-planners in developing countries. Commonly practised resource allocation criteria depend on some trivial statistics, hence critical factors such as human mobility are often ignored in making health decisions. In this work we propose to incorporate inter-regional mobility factor into the decision-making process. Starting from the well-known compartment models for epidemic transmission, we formulate a nonlinear optimisation problem for the regional allocation of resources, aimed at minimising the total number of infectious persons in the country. Computational challenges in finding the global optimum to this problem are overcome by restating it in the form of a separable program, which is eventually reduced down into an efficiently solvable mixed-integer linear program. We derive numerical results by applying our solution techniques to relevant data on dengue transmission in Sri Lanka. Finally, we interpret the results and show that resource allocations are inadequate unless the mobility factor is taken into account.
Keywords: resource optimisation; separable programming; linear programming; epidemic models.
Evaluation of Students University Selection Decision-Making using an Instilled Fuzzy AHP Approach
by Neha Gupta, Mohini Agarwal, Pratibha Garg
Abstract: The purpose of this study is to identify and rank the potential factors that can benefit the students in making an optimal decision for university selection in learning process. To achieve this purpose, informational architype, along with the questionnaire, was circulated, which was followed by analysing the responses. For the data collection purpose, a structured questionnaire was constructed, and responses of 100 prospective students of Indian origin who are likely to take admission in universities were recorded. After reviewing the literature, six prominent factors have been considered, and AHP followed by FAHP techniques have been employed for computing weights corresponding to assumed factors. The results indicated that the highest weightage had been given to location followed by fee structure in both the cases. Further, utility theory has been used, which shows the superiority of FAHP over AHP analysis.
Keywords: university selection; decision-making; analytical hierarchy process; AHP; fuzzy analytical hierarchy process; FAHP; utility theory.
A linear programming model for airline schedule recovery after disruption
by Jakob Kotas
Abstract: We present a decision support framework for optimal flight rescheduling on an airlines day of operations under unanticipated system disruption. We consider disruptions which add an unforeseen need to extend each aircrafts turnaround time on the ground, not necessarily uniformly across all flights or airports in the system. Our model optimally reschedules remaining flights of the day to minimise system delays and cancellations. The model is formulated as a mixed integer linear program. We prove that structural properties of the model allow it to be decomposed into a finite set of linear programs, and a computationally tractable algorithm for its solution is described. The model is solvable exactly and quickly, even for large airlines. Numerical simulations are presented for a case study of a winter weather event impacting Horizon Air, a regional airline based in the Pacific Northwest of the USA.
Keywords: decision support framework; disruption management; scheduling; airline scheduling; airline operations; linear programming; mixed integer linear programming; winter weather; snow; de-icing.
Transient analysis of various vacation interruption policies in a Markovian queue with differentiated multiple vacations
by A. Azhagappan, T. Deepa
Abstract: Two different types of interruptions (partial and complete) of servers vacation are discussed in this research work along with two different types of vacations (types 1 and 2). The transient analysis of an M/M/1 queueing model with differentiated multiple vacations, partial and complete interruption of vacations is carried out. Two types of vacations are studied in this research work. Type 1 vacation is taken after serving all the customers in the system exhaustively. Type 2 vacation is resumed after returning from type 1 vacation and finding the empty system. Partial interruption is the one in which the interruption happens only in type 2 vacation whereas complete interruption can occur in both types 1 and 2 vacations. The system size distributions are derived using generating function and Laplace transforms under transient case. The average and variance are also obtained. Further, numerical simulations are presented.
Keywords: the M/M/1 queue; differentiated multiple vacations; partial and complete interruption of vacations; transient probabilities.
Improving healthcare services in Trauma Emergency Centre for patient safety under COVID-19 pandemic crises
by Dilbagh Panchal
Abstract: This work presents an application of structured decision support model for improving health service related quality in Indian Trauma Emergency Centre (TEC) under COVID-19 pandemic crisis. Fuzzy failure mode and effect analysis (FMEA) tool built decision support model has been applied for pinpointing the most precarious causes/barriers which result in poor health service quality. Various causes/barriers responsible for poor service quality associated with TEC has been listed under FMEA sheet thorough carrying a brainstorming session with hospital management. Feedback in the form of linguistic ratings were filled by the three experts against three risk elements. For overcoming the drawback of traditional FMEA approach in term of uncertainty/vagueness effect and same ranking problems, fuzzy FMEA was applied and the fuzzy output-based rankings are equated with traditional FMEA approach-based results in order to take necessary action for minimising the total service time for patients safety during this pandemic period.
Keywords: trauma emergency centre; patient safety; COVID-19; health service; fuzzy FMEA; service time.
Integrated Bioethanol-Gasoline Supply Chain evolved by changing US government policies
by Davoud Ghahremanlou, Wieslaw Kubiak
Abstract: COVID-19 travel restrictions caused gasoline consumption reduction. Global warming and crude oil dependency had already driven policymakers to make policies to reduce consumption of gasoline. The US had created policies to regulate bioethanol production and blending with gasoline. Although these regulations created opportunities, they also placed new burdens on the obligated parties. The effect of the policy change on the integrated bioethanol-gasoline supply chain (IBGSC) is therefore important for both government and business to study to reduce bankruptcies in current market refineries and bio-refineries. To that end, we extend the IBGSC studied by Ghahremanlou and Kubiak (2020a) to include both first and second generation bioethanol, import and export, and existing infrastructure. We develop a two-stage stochastic programming model. Solving this model leads toward solving NP-hard problems, therefore, we develop an algorithm and overcome the computational complexity. The ELM can be employed to evaluate sustainability of the IBGSC under different policies.
Keywords: COVID-19; supply chain management; operations management; location-allocation; sustainability; stochastic programming; oil war.
A Mixed-Integer Quadratic Programming Production-Transportation Problem
by Dominic Otoo, Bernard A. Adjei, Sampson T. Appiah
Abstract: One economic challenge encountered by most companies that produce and haul their local products to independent distributors is accurately identifying the optimal routes to each distribution centre and assigning production machinery. The authors in this paper have collaboratively developed a mixed-integer quadratic model that optimally assigns machines and vehicles to produce and properly distribute goods to multiple distributors in 105 locations dotted across the 16 regions of the country based on their demand constraints. Our formulated model and analysis show that the production cost accounts for 0.7933 and transportation cost accounts for 0.2066 of the total cost. Our results have convincingly shown a cost reduction of 10% and 25% respectively in terms of production and transportation cost as compared to the cost currently operated by the two local factories under consideration.
Keywords: optimal; integer programing; production; transportation; distributors.
A two-level supply chain with price sensitive random demand, random yield, inspection, and rework process
by Farzaneh Mohammadia, Maryam Esmaeili, Jiang Zhang
Abstract: This paper studies a two-level supply chain consisting of a manufacturer and a retailer. The manufacturers production output follows a random process due to the presence of defective goods. The retailer faces random price dependent customer demand. We propose that the manufacturer can reduce the number of defective items manufactured by performing inspection and rework. We first consider both decentralised and centralised supply chain models to determine the manufacturers production size, the retailers order quantity, the manufacturers rework cost, and the retailers sales price, as well as the retailers and the manufacturers expected profit. We then propose a buy-back contract to coordinate the supply chain. We also use numerical examples to illustrate our findings and perform sensitivity analysis on the price elasticity of the demand and tensile coefficient of rework cost.
Keywords: random yield; random demand; rework process; pricing; supply chain; buy-back contract.
A Metaheuristic for the Multiple Minimum Latency Problem with the Min-Max Objective
by Ha-Bang Ban
Abstract: The multiple minimum latency problem with the min-max objective (mMLPMM) is an extension of the multiple minimum latency problem (mMLP). The mMLPMM requires to find a tour that aims to equally distribute the latency among routes by minimising the maximum route latency. To solve medium and large size instances, an effective metaheuristic algorithm is introduced, which combines greedy randomised adaptive search procedure (GRASP) for an initial solution construction, and general variable neighbourhood search (GVNS) for solution improvement. The proposed algorithm is tested on the benchmark instances derived from the literature. The results indicate that the GRASP-GVNS can produce efficient and effective solutions for the mMLPMM at a reasonable computation time.
Keywords: multiple minimum latency problem with min-max objective; mMLPMM; greedy randomised adaptive search procedure; GRASP; general variable neighbourhood search; GVNS; metaheuristic.
Dynamic Programming approach to achieve higher view-count for YouTube Videos
by Mohammed Shahid .Irshad, Adarsh Anand, Sankar Kumar Roy
Abstract: Broadcast media telecasts their programs at fixed timing, which forces the viewer to be presented at the time of broadcast whereas online streaming platforms allows viewers to watch videos any time. YouTube being the free streaming platform attracts lot of viewers where short videos are uploaded. With its growing popularity content creators have started uploading series of scripted or non-scripted content (video) in episode forms known as a web series. A web series usually has 5 to 10 episodes, and each episode is uploaded independently. The producers desire maximum view-counts with minimum promotional expenditure on each web series. This paper presents an optimisation modelling framework for budget allocation in order to achieve a greater number of view-counts. The proposed framework takes into consideration the aspiration level for the episodes wherein; dynamic programming approach has been utilised to numerically illustrate the validation on two web series on YouTube.
Keywords: budget allocation; dynamic programming; view-count; web series; YouTube.
An Optimization-Simulation Framework for Integrated Inventory and Cash Replenishment Problem of Automated Teller Machines in India
by Ankush Kamthane, Prashant Singh, Ajinkya N. Tanksale
Abstract: This work is motivated by the problem of managing inventory and the optimal replenishment schedule for a network of automated teller machines (ATMs) in India The objective is to minimise the occurrences of shortages at the ATMs and in turn to achieve a higher service levels while minimising the cost of holding inventory and replenishment of ATMs The problem is casted as a rich variant of inventory routing problem with several practical restrictions such as maximum inventory at the ATMs. A two-phase iterative decomposition heuristic is proposed to efficiently solve the practical size problem instance. The computational experiments based on synthetic data are conducted to assess the efficiency and effectiveness of the proposed solution approach and a case of Varanasi city in India is presented for the analysis. The results shows the effectiveness of our proposed approach over the conventional replenishment policies.
Keywords: automated teller machine; ATM; inventory routing problem; IRP; mixed-integer programming; heuristic; simulation.
Application of Fintech in Financial Inclusion: A Bibliometric Review
by S.M.Rakibul Anwar, Riduanul Mustafa, Md. Abul Kalam Azad
Abstract: This study examines the literature on fintech application in financial inclusion applying a citation mapping-based review technique-bibliometric analysis. The results of bibliometric review are then manually validated with content analysis. A total of 46 published documents from Scopus database are examined. Major findings from bibliometric review reveal three distinct research areas in literature: 1) generic application of fintech; 2) methodological and implication of fintech in credit scoring; 3) country performances. Future research directions are also identified.
Keywords: fintech; financial inclusion; bibliometric; financial exclusion.
A Modified Method for Solving the Unbalanced TP
by Anju Khandelwal, Avnish Kumar
Abstract: Most of the methods suggested for the unbalanced transportation problems, in the literature are based on an adding of dummy source/destination with zero cost to make it balance transportation problem first and then to obtain the basic feasible solution (BFS). The present paper suggests a modified algorithm for finding a BFS to an unbalanced transportation problem through which we get the optimum solution without adding the dummy source/ destination. The method is presented in an algorithmic form and implemented on several sets of input data to test the performance and effectiveness of the algorithm. A comparison is also made with the existing approach and it is found that the suggested algorithm shows better performance.
Keywords: unbalanced transportation problem; UTP; Vogels approximation method; VAM; initial basic feasible solution; IBFS; basic feasible solution; BFS; optimal cost.
Decision Making and Martial Arts
by José Soeiro Ferreira
Abstract: Martial arts (MAs) are a global training system that goes far beyond physical preparation and self-defence. They have been known for a long time, and their wisdom and impact are impressive. The paper illustrates matters about MAs which are relevant to decision making (DM). The recognition of the limitations of the sole dependence on physical ability (hard approaches) is a breakthrough in MAs. The pillars of body and technique are not enough to reach a global vision and overcome severe problems. MAs are committed to mastering faculties linked to intuition, emotions, and thought-free operations, signifying the pillar mind. These revelations have insightful implications for DM and the promptness in approaching the growing complexity of decision problems. Special attention is devoted to the mind, representing a soft paradigm, emphasising the human dimension, integrating intuition and complying with ethics. Finally, the paper delineates a MAs way to improve DM as science and art.
Keywords: decision making; martial arts; operational research; hard and soft methodologies; intuition; emotions; ethics.
Locating a Rectangular Barrier Facility on the Plane: A Bi-Objective Approach
by Mustafa Canbolat, George O. Wesolowsky, Michael Von Massow
Abstract: We study the problem of finding a minimax location for a rectangular barrier facility on the plane and simultaneously minimising the interference of the barrier facility to the interactions among the existing facilities using rectilinear distances. This provides an ex post opportunity to modify an existing network or layout while minimising the disruption. The problem is formulated as a bi-objective problem and a mixed integer program is proposed as a solution methodology. A simulated annealing algorithm is presented for an extension of the problem where expropriation or removal of existing facilities is also possible. We consider expropriation or removal of existing facilities only if such policy is necessary or cost-beneficial.
Keywords: planar facility location; facility layout; barriers; expropriation; optimisation; heuristics.
Redundancy optimization for tandem production systems under queueing and availability constraints
by Fong-Fan Wang
Abstract: Equipment selection is an important issue during the initial phases of implementing a production system. In this paper, one type of product manufactured on a production line composed of several stages with redundant and unreliable machines is studied. Assume available version of machines with respective cost and operating characteristics are available for each subsystem, the objective is to minimise the purchase cost subject to average system availability and total waiting time constraints. We propose two techniques for evaluating the studied system. Using simulation, we justify that matrix analytical method can approximate the system behaviour better than another method based on Allen-Cunneen approximation. We employ three meta-heuristics, including genetic algorithm, particle swarm optimisation and simulated annealing to optimise the system structure. We provide numerical examples for performance evaluation and comparison of the efficiency and efficacy of the proposed optimisation methods.
Keywords: tandem production system; redundancy optimisation; matrix analytical method; metaheuristics.
A new Secant-like quasi-Newton method for unconstrained optimization
by Issam A.R. Moghrabi
Abstract: The secant equation traditionally constitutes the basis of quasi-Newton methods, as the updated Hessian approximations satisfy the equation on each iteration. Modified versions of the secant relation have recently been the focus of several papers with encouraging outcomes. This paper continues with that idea where a secant-like modification that utilises nonlinear quantities in constructing the Hessian (or its inverse) approximation updates is derived. The technique takes advantage of data readily computed from the two most recent steps. Thus, it offers a substitute to the secant equation to produce better Hessian approximations that result in accelerated convergence to the objective function minimiser. The reported results provide adequate evidence to suggest that the proposed method is promising and deserves attention.
Keywords: quasi-Newton methods; secant-like methods; BFGS; unconstrained optimisation; multi-step methods.
An inventory model for perishables with fixed storage life and diminishing ability to buy in their life expectancy.
by SAURABH SRIVASTAVA
Abstract: In present market scenario, health-conscious customers embrace a policy to purchase a perishable product with more storage life as it is fresher and can be stored for successful time. Additionally, a large variety of goods in market influence customers to buy the most recent and quality improved items propelled by the companies. In this paper, these two relevant factors are incorporated and an optimal inventory model for the demand pattern depending on the willingness of buyers under fixed storage life has been developed. The demand process includes the willingness of customers to buy such items subject to their desired degree of satisfaction. To study such demand fluctuation, a stochastic mathematical model using the Gaussian distribution has been presented. The optimised values of parameters have been determined and the results are analysed with the help of numerical example. A sensitivity analysis for the involved parameters over optimal results is also provided.
Keywords: inventory; stochastic model; storage life; perishable; Gaussian distribution; willingness; life expectancy.
A Fuzzy Random Periodic Review Mixture Inventory Model with Backorder Price discount
by Wasim F. Khan, Oshmita Dey
Abstract: In this paper, a periodic review inventory model with a mixture of backorders and lost sales is developed under mixed fuzzy random environment. It is assumed that the supplier provides some price discount to control the backorder rate and gives an incentive to the customers to wait for the arrival of their orders rather than take their orders elsewhere. The annual customer demand is considered to be continuous fuzzy random variable following normal distribution. The model is analysed under three scenarios no price discount, fixed price discount and controllable price discount. An algorithm is presented to simultaneously determine the optimal values of the review period, the target inventory level and the backorder price discount so that the total annual cost is minimised. Numerical examples show that the case of controllable backorder price discount leads to the system incurring lowest operational costs.
Keywords: inventory; periodic review; backorder price discount; continuous fuzzy random variable; normal distribution.
Novel Approach to Data Envelopment Analysis
by Drinko Kurevija
Abstract: This article analyses the performances of the Austrian Research Promotion Agencys (ARPA) general program by applying a novel approach to data envelopment analysis (DEA) namely the adjusted DEA (A-DEA). Considering the previous findings of Sowlati and Paradi (2004) by defining a new practical frontier and utilising management input, a modified linear programming model and a methodology for improving the efficiency of empirically efficient units was applied. The aim was to find the output for the novel different units in order to identify an alternative frontier of both already empirically efficient and these new DMUs considering the performances of ARPAs general program.
Keywords: data envelopment analysis; DEA; novel DEA; unobserved DMUs; weight restrictions; multicriteria decision making; stochastic frontier analysis; programs; projects; efficiency.
A game theory framework for newly launch greening product in two-echelon supply chain
by Sukhendu Bera, Raghu Giri, Dipak Kumar Jana, KAJLA BASU, Manoranjan Maiti
Abstract: A two-echelon supply chain model is considered where one manufacturer and one retailer reduce the customers sensitivity to the product price and stimulate the demand of the product by introducing facilities such as products greenness, service level and promotional effort. They share the costs jointly on the above facilities following some agreements. The models are formulated as profit maximisation problems for the whole system and chain members under centralised and decentralised decision scenarios and solved using game theoretical approach. As particular cases, several models with greenness, service level and promotional effort separately (one or two facilities at a time) are formulated and solved. Finally, numerical experiments are conducted and some managerial decisions are presented from the optimal results and sensitivity analyses. It is demonstrated that the greenness, service level and promotional effort activities stimulate higher demand and fetch more profits for supply chain and its members.
Keywords: supply chain; greening investment; promotional effort; service level; Stackelberg game.
Analyzing a queueing network of the emergency department with deteriorating health in post-disaster situations
by Sara Benvidi, Tooba Asghari, Amir Aghsami, Fariborz Jolai
Abstract: Providing appropriate healthcare services in emergency departments (ED) after a disaster is a good way to reduce casualties. This study attempts to model an ED as a three-stage queue with a deteriorating patients health condition where the system experiences a disaster. Triage has been considered as the primary stage which classifies patients into two types. The paper aims to present the best budget planning and capacity planning to minimise total death and waiting times. Queueing networks are used to model the mentioned situation. Finally, three mathematical formulations are accompanied by numerical experiments. We observed the behaviour of each model to support managers in policy makings. We conclude that exigent plays a significant role in the total death number and service rate of triage and semi-urgent, significantly impacting the total waiting time.
Keywords: emergency department; healthcare; Markovian queueing systems; budget and capacity planning; triage; deterioration; disaster.
Lot Sizing Model for multiple products over Finite Planning Horizon under the Effect of Learning and Time-Value of Money with cap-and-trade and carbon tax regulations: A Fuzzy Framework
by Narendra Kumar, Rachna Kumari, Dharmendra Yadav
Abstract: This study presents a multi-item manufacturing process by assuming that the demand for different products depends on the selling price and awareness program. The manufacturer adopts a system improvement program to reduce the defective items and an investment policy on green technology to curb carbon emission. Article also explores the influence of learning on unit production time. Impreciseness in different costs is handled with fuzzy set theory. The optimal solution is obtained with the help of the classical optimisation technique. Further, obtained results indicate the advantage of carbon regulation policies as carbon tax and carbon cap and trade policy. The result also shows a significant improvement in the system's profit by considering the learning effect. Whole of the study is carried out under the impact of inflation. The developed model is investigated further with the help of a numerical example. In the end, sensitivity analysis is performed for important parameters.
Keywords: multi-items; learning effect; promotional activity; selling price dependent demand; imprecise costs; signed distance method; inflation; finite planning horizon.
A Simplified Multi-Granular Linguistic Term Sets Method
by Harliza Mohd Hanif, Daud Mohamad, Rosma Mohd Dom
Abstract: The multi-granular concept involves many parts of a complex system or model. Since the late 1990s, many researchers have started to incorporate multi-granular concepts in their research areas. This paper focuses on the use of multi-granular linguistic (MGL) term sets in the decision-making method. The use of the MGL method in decision-making may impose a high level of complexity since it offers flexibility to the decision maker. The flexibility given is by determining the output of the cardinality. Complexity in a method may impose disadvantages in terms of, for example, inaccuracy of outcomes, loss of information, and time consumption. Hence, a simplified multi-granular linguistic term sets (SMM) method is proposed with a lower complexity level to overcome the disadvantages of complexity. This was achieved by introducing a parallel process of cardinality (PPC) into the simplified multi-granular linguistic term sets method (SMM). After proposing the simplified multi-granular linguistic term sets method, the complexity level of this method is compared with other methods based on the relative complexity index (RCI).
Keywords: cardinality; multi-granular; parallel-process; simplified.
A new model for physician assignment based on fuzzy rules extraction from climatic factors
by Sima Hadadian, Zahra Naji Azimi, Nasser Motahari Farimani, Behrouz Minaei-Bidgoli
Abstract: The number of patients should be predicted to meet the physicians demands in hospitals. In this study, a new multi-objective physician assignment model was designed based on the number of the patients estimated by the climatic factors. The number of patients was predicted through multiple linear regression (MLR) and fuzzy inference system (FIS). In the FIS, the feature selection was performed by the genetic-K-nearest neighbours algorithm. Then, fuzzy rules were extracted using fuzzy associative classification. After predicting the number of patients, the physician assignment model was designed. The case study is a paediatric hospital with four wards. The results indicated some medical fuzzy rules based on climatic factors. In addition, RMSE and MAE, as compared with MLR in all hospital wards, had a lower value in the FIS. Finally, the advantage of the assignment model could be attributed to its sensitivity to changes in the number of the patients.
Keywords: multi-objective model; physician assignment; fuzzy associative classification; FAC; fuzzy inference system; FIS; genetic-K-nearest neighbours algorithm; multiple linear regression; MLR.
An Inventory System Using Preservation Technology Investment for Ameliorating and Deteriorating Items with Ramp-Type Demand Dependent on Price and Time and Partial Backlogging
by AJOY HATIBARUAH, Sumit Saha
Abstract: This article describes an inventory model developed for ameliorating items considering ramp type demand dependent on price and time with partially backlogged shortages. Ameliorating items such as livestock are raised in the farm when their size and quantity are small. The quantity and size of these items increase due to their high growth rate. However, their quantity may decrease due to certain diseases or death. Amelioration rate is described by Weibull distribution. Preservation technology is adopted to reduce the deterioration effect. Ramp type demand results in two possible cases, for which two different models were developed. Our goal is to estimate optimal preservation technology cost, selling price and the time at which maximum inventory and shortage occurs while total cost is minimised. Some numerical examples for two different cases are solved. Impact of the parameters on optimal solution is analysed through sensitivity analysis while the results obtained are discussed accordingly.
Keywords: inventory; amelioration; deterioration; price and ramp-type time dependent demand; preservation technology investment; partial backlogging.
A technique to solve mixed strategy non-cooperative zero sum games with more than two players
by RANJAN GUPTA, Debdip Khan
Abstract: In this paper, we have proposed a technique, capable of solving m
Keywords: game theory; N-persons mixed strategy game; two-dimensional representation; two persons zero sum game; genetic algorithm.
Restructuring of units under inter-temporal dependence: Method and application
by Mona Avand, Seaid Ghobadi
Abstract: This paper deals with the generalised restructuring decision making units under inter-temporal dependence data. An important issue for generalised restructuring of a set of decision making units is the estimation of the input and output levels inherited from pre-restructuring decision making units between post-restructuring decision making units to achieve full dynamically efficiency levels. This issue, the input and output-estimation for achieving efficiency targets, is investigated via the inverse data envelopment analysis concept. An effective method is provided that allows managers to incorporate their preference in targets setting of a restructuring for saving/producing specific input/output levels in each time period of the assessment window as much as possible. Sufficient conditions are derived for input and output estimation using multiple-objective programming problems. The applicability of the proposed method is illustrated through a banking sector example.
Keywords: data envelopment analysis; DEA; inverse DEA; generalised restructuring; inter-temporal dependence; multiple-objective programming; MOP.
Two-Commodity Multi-Server Queueing-Inventory System with Compliment Product and Classical Retrial Facility
by Jeganathan Kathirvel, Nithya M, C. SUGAPRIYA, Selvakumar Subramanian
Abstract: This article explores a two-commodity stochastic queueing-inventory system (TCSQIS) along with a multi-server and a classical retrial facility. In this two-commodity, the first one is called a primary product (PP) and the second one is called a complimentary product (CP). The TCSQIS provides a multi-server service facility to an arriving customer in order to reduce the loss of arrival and increase more sales and profit. Suppose the arriving customer sees that all the servers are engaged or there are no sufficient products in the system, they go to an infinite orbit compulsorily. The customers in orbit can approach the system under classical retrial policy, whenever they confirm that the system must consist of at least one server that is free and positive stock. The stationary probability vector is obtained by the matix-geometric approach (MGA). Further, adequate examples are provided to explore the proposed model.
Keywords: multi-server; compliment product; infinite orbit; classical retrial policy; waiting time.
Advanced Payment Strategy for EOQ Model regarding Perishable Product With Maximum Lifetime,Customer Return, Preservation Technology and Partial backlogging
by Ravendra Kumar, Ravish Kumar Yadav
Abstract: Many products, like fruits, vegetables, etc. have a certain life that depends on the preserving conditions and also the demand of these products depends on their life. Selling price and the investment in a preservation mechanism are the most important factors in inventory management. An economic order quantity model is proposed focusing on perishable products having a certain lifetime. A preservation mechanism has been implemented to extend the products lifetime. Two different models with or without shortages are presented here. Concavity of objective function is established using several theorems. Developed model is validated with the help of numerical examples. Sensitivity is also carried out. The results show that the retailers profit reduces when dealing with products for which customers are more concerned about the products lifetime. The findings also suggest that in order to increase profit, retailers should design an inventory policy that controls purchase costs and interest.
Keywords: advanced payment; EOQ; perishable product; customer return; preservation technology; partial backlogging.
Investigation of Production Systems for two-level Supply planning with Breakdown and Lead Times Uncertainties
by Parimah Zandi, Heibatolah Sadeghi, Hiwa Farughi
Abstract: This paper investigates the supply planning of two-level and multi-period inventory control with stochastic lead time and random machine breakdown. Due to the probability of lead time, the actual lead time may be longer than the planned time in each production cycle, which will delay the delivery of the final product to the final customer, and it is also possible that the final product will be ready to be delivered to the customer sooner than the specified time, in which case the product is maintained and delivered to the customer at the specified time, which imposes additional maintenance cost on the production system. Also, due to the random machine breakdown, the machine may break during production or outside the production cycle. Demand for the final product and the policy of supplying demand is considered as periodic order quantity. The purpose of the problem is to determine the planned lead time and time interval between production orders based on periodic order quantity policy and uses the genetic algorithm to minimise the total system costs. Finally, a numerical example is explained, based on which the main parameters of the proposed model are analysed.
Keywords: planned lead time; stochastic lead time; order quantity policy; maintenance.
Credit rating ranking of Iranian Banks based on CAMELS and Hybrid Multi-Criteria Decision Analysis methods in uncertain environment
by Amir Karbassi Yazdi, Precious Okereke, Peter F. Wanke, Seyed Arash ShahrAeini, Amir MehdiAbadi
Abstract: This research aims to rank Iranian banks by CAMELS and multi-criteria decision analysis (MCDA) methods in uncertain environments. Ranking banks can lead to a better understanding of how customers select them and use their services. Since there is close competition between private and government banks in Iran, the most popular rating system (CAMELS) can help customers gain a better understanding of their situation. The CAMELS method consists of a rating based on bank performance factors. For finding the best bank in Iran once the CAMELS factors are considered, banks are then ranked by the COmbined COmpromise SOlution (CoCoSo) method, which also requires the stepwise weight assessment ratio analysis (SWARA) method to be used. The environment, however, is changing, thus affecting decision makers (DMs), so using uncertainty methods such as Pythagorean fuzzy numbers (PFN) is essential, which helps DMs make better decisions. The sample population of this research is eight public banks in Iran. The result indicates the best bank based on CAMELS and MCDA methods in uncertain environments with the result also pointing out how banks with a lower performance can do benchmarking to improve their performances according to CAMELS factors.
Keywords: CoCoSo method; SWARA; CAMELS method; bank credit rating; Pythagorean fuzzy numbers; PFN.
Analysis of MAP/PH(1), PH(2), PH(3)/1 Queueing System with Two Modes of Heterogeneous Service, Standby Server, Vacation, Impatient Behavior of Customers, Additional Service, Startup Time, Breakdown and Phase Type Repairs
by AYYAPPAN Govindan, Thilagavathy Karthikeyan
Abstract: In this article, we consider a single server queue in which customers arrive according to the Markovian arrival process (MAP) and their corresponding two modes of service based on phase-type (PH) distribution. While the main server is offering either two modes of service or additional service, the server may affect by breakdown immediately go for the repair process. At that moment, the service process switches over to the standby server until the main server rejuvenated from the phase-type repair. When vacation completion epoch, the main server will do the startup process. Using the Matrix-Analytic method, we investigated the total number of customers in the system under the steady-state probability vector. We examined the stability condition, busy period and characteristics of some performance measures of the system are discussed. Numerical results are tabulated and graphical representations are provided for a clear view of our model.
Keywords: Phase-Type Distribution; Markovian Arrival Process; Standby Server; Impatient Behavior; Additional service.
Multi-Objective Faculty Course Timeslot Assignment Problem for Tutorial and Laboratory Courses
by Sunil Bhoi, Jayesh Dhodiya
Abstract: This study applied a multi-objective zero-one integer programming model to resolve the university timetabling problem of assigning timeslots to faculty member for tutorial and laboratory courses. The model helps prepare an efficient and effective timetable by optimising the satisfaction levels of faculty members, administrators, and students. It ensures that no conflict occurs between tutorial and laboratory courses and their proper distribution across days and sessions. Furthermore, the model assigns all batches of the same course to one faculty member to save preparation/laboratory setup time. Appropriate scheduling allows each batch to utilise their time for self-study courses, library, and extracurricular activities. The model systematically incorporates two-hour laboratory courses in two consecutive break-free timeslots and the proper utilisation of the library and preparation for self-study courses by students. The model was applied to a technical institute using hypothetical data, and effectual and feasible schedules were generated using fuzzy programming. The solutions were obtained using LINGO 18.0 software.
Keywords: timetabling; university course scheduling; multi-objective programming; zero-one linear programming; fuzzy programming technique.
A novel inverse DEA model for restructuring DMUs with negative data
by Seaid Ghobadi, Khosro Soleimani, Ehsan Zanboori
Abstract: One of the important issues in generalised restructuring of a set of units is the identification of the input and output levels from a new set of post-restructuring units. This paper deals with the generalised restructuring of decision making units (DMUs) in the presence of negative data for achieving efficiency targets. A novel inverse DEA model is proposed for modelling the generalised restructuring of a set of DMUs in the presence of negative data. Sufficient conditions are given for estimation of inputs and outputs of the new set of post-restructuring units to realise efficiency targets. A numerical example is employed to illustrate the developed theory.
Keywords: data envelopment analysis; DEA; inverse DEA; multiple objective programming; MOP; generalised restructuring; efficiency; negative data.
Pascals Triangle Graded Mean Defuzzification Approach For Solving Fuzzy Assignment Models by Using Pentagonal Fuzzy Numbers
by Zeina Mohammed
Abstract: The fuzzy assignment models (FAMs) have been explored by various literature to access classical values, which are more precise in our real-life accomplishment. The novelty of this paper contributed positively to a unique application of pentagonal fuzzy numbers for the evaluation of FAMs. The new method namely Pascals triangle graded mean (PT-GM) has presented a new algorithm in accessing the critical path to solve the assignment problems (AP) based on the fuzzy objective function of minimising total cost. The results obtained have been compared to the existing methods such as, the centroid formula (CF) and centroid formula integration (CFI). It has been demonstrated that operational efficiency of this conducted method is exquisitely developing an optimal solution (Opt. Sol.) depending on the corresponding path by the new tender algorithm.
Keywords: centroid formula; centroid formula integration; CFI; fuzzy assignment models; FAMs; optimal solution; Opt. Sol.
Pricing and Ordering Strategy for New Product and Buyback Strategy for Used Product from Retailers Point
by DHARMESH KATARIYA, Kunal Shukla
Abstract: Today environmental spectrums are much considered while purchasing a new product because of global awareness about sustainability of environment, hence an interest for use of restored products has increased. The retailer is a decision-maker; retailer sells a new product to the consumers and also collects the used sold products for reselling. In this deteriorating inventory model, the demand rate of new products is a nonlinear function and demand rate of used buyback products is linear function of selling price and time-dependent respectively. Shortages are allowed and the unsatisfied demand is partially backlogged. The objective is to maximise total profit per time unit for a retailer concerning to optimise selling price, order quantity for a new product, and quantity of used buyback products simultaneously. Global optimality is verified by Hessian matrix method and graphically. This model is explained through a numerical example, sensitivity analysis, and managerial insights. Ultimately, some concluding remarks with future scopes are discussed.
Keywords: inventory; used buyback product; price dependent demand; deterioration; partial backlogging.
An Adaptive Large Neighborhood Search Algorithm for Blocking Flowshop Scheduling Problem with Sequence-Dependent Setup Times
by Faezeh Bagheri, Morteza Kazemi, Ardavan Asef-Vaziri, Mahsa Mahdavisharif
Abstract: Flowshop scheduling problem (FSP) belongs to the classical combinatorial optimisation problem and takes different forms under different production conditions. To make the general form of FSP closer to the real production environment, two assumptions, including blocking and sequence-dependent setup time, were added. The first attempt of the current research work is proposing a mathematical model according to two different viewpoints about blocking occurrence affected by sequence-dependent setup time that try to use the dead time (blocking or idle time) for setting-up the next job. Due to the complex intrinsic of combinatorial problems, achieving the exact result on a large-scale through a mathematical model is almost complicated. The second attempt is developing an adaptive large neighbourhood search algorithm to solve the problem on a large-scale which is accelerated by a new constructive heuristic algorithm. Extensive computational experiments on various size problems support the efficiency of the proposed algorithms.
Keywords: flowshop; blocking; sequence-dependent setup time; heuristics algorithm; adaptive large neighbourhood search algorithm; mathematical modelling.
On the scheduling of handling equipment in automated container terminals
by Iñigo L. Ansorena
Abstract: This paper deals with the application of the flow shop scheduling problem (FSSP) to automated container terminals. After the description of operations between the quay line and the storage yard we analyse the flow of containers through six well established heuristic methods. Additionally, we apply a full enumeration mechanism to solve the FSSP. This technique enumerates all permutation schedules and picks the best one based on the specified criterion. A numerical illustration is given to clarify the application of FSSP techniques to container terminals. The paper suggests that the selection of the best heuristic is crucial to increase productivity and achieve goals, since it allows time savings around 20%-30% depending on the method used.
Keywords: flow shop; sequencing problem; container terminals; heuristic method; automation; guided vehicles; stacking cranes; quay cranes; operation time; time savings.
A DEA model towards efficiency estimation of biomass energy production of agro-energy districts
by Anna Kalioropoulou, Basil Manos, Thomas Bournaris
Abstract: In this work, the data envelopment analysis (DEA) is applied for the estimation of relative efficiency in biomass energy production and for optimal organisation of farm planning in accordance to EU goals for renewable energy sources. Specifically, a DEA model with five inputs and one output was employed at the seven prefectures of Northern Greece. The inputs used for the purpose of this study are the main factors of agricultural production, i.e., the land available, the variable costs, the available tractors, the fertilisers and the labour used. The output is the electric energy from the biomass of crop residues and it is consistent with EU objectives for renewable energy sources. The application of the DEA model revealed four prefectures as relatively inefficient and three as relatively efficient. From the empirical analysis, a reorganisation and a better allocation of inputs for the inefficient prefectures is suggested.
Keywords: relative efficiency; data envelopment analysis; DEA; biomass energy.
Analysis of MAP/PH/1 retrial queue with constant retrial rate, working vacations, abandonment, flush out, search of customers, breakdown and repair
by G. Ayyappan, R. Gowthami
Abstract: A retrial queueing model in which the inter arrival times follow Markovian arrival process (MAP), the service times follow phase type distribution and the remaining random variables follow exponential distribution is studied in this paper. We use the matrix analytic method to study the resulting GI/M/1-type queueing model in the steady state. Some performance measures are enumerated. The analysis of the model has been done numerically and graphically.
Keywords: Markovian arrival process; MAP; phase type distribution; retrial queues; orbital search; working vacation; breakdown and repair.
Non-dominated sorting genetic algorithm-II for locating emergency bases to minimise mean and standard deviation of service time
by Hamid Reza Golmakani, Mahtab Eskandar
Abstract: Pre-hospital emergency is one of the most important issues in healthcare systems. One of the items that strongly influence the performance of emergency services is the location of emergency bases since the service time plays a key role in the success of an emergency mission. In this paper, a binary nonlinear programming model is proposed for locating emergency bases. The goal is to minimise the mean and standard deviation of emergency service time while satisfying the relevant constraints. To cope with the computational complexity in obtaining optimal solutions, non-dominated sorting genetic algorithm (NSGA-II) is proposed. The proposed NSGA-II approach is applied for locating emergency bases in a part of Tehran metropolis and non-dominated solutions are presented. Sensitivity analysis on the available budget is also presented.
Keywords: pre-hospital emergency; nonlinear integer programming; emergency bases locating; Bi-objective functions; service time.
Duality of control problems in general Banach spaces
by Pramoda Kumar Behera, Saroj Kumar Padhan, Chandal Nahak
Abstract: Control problems have been given a special attention to the theory of optimisation, which is concerned with problems involving infinite dimensional cases. Control problems along with various types of their duals are described in general Banach spaces. Under convexity assumptions on functionals, several duality (weak, strong and converse) results are established between control primal and the corresponding Mangasarian type dual problem. Again, the Mond-Weir type duality model is constructed to weaken the convexity condition to pseudo-convexity and quasi-convexity. Many nontrivial examples are given to support the efficacy of the new findings. It is found that some of earlier results are the special cases of the present investigations.
Keywords: control problems; convexity; Mangasarian type duality; Mond-Weir type duality.
Analysis of unreliable bulk queueing system with overloading service, variant arrival rate, closedown under multiple vacation policy
by G. Ayyappan, M. Nirmala
Abstract: In this article, an unreliable single server bulk queueing model with overloading service, variant arrival rate, closedown under multiple vacations are considered. The arrival rates of the units are different and depends upon the server status. On service completion epoch, if the queue length is less than 'a' then the server perform closedown work. Following the closedown, the server leaves for multiple vacations of random length. We incorporated the overloading concept for the server which is assured in various practical applications. When the server is in working modes, breakdown may occur randomly at any instant during essential/overloading service. The repair job of broken down machine is done immediately and the server returns to render its remaining service. We derived the probability distribution of queue length at a departure and random epoch using supplementary variable technique. Various performance indices namely the expected length of the queue the expected waiting time in the queue are obtained. Stability condition and steady-state probabilities are also established. In order to match our investigation with the earlier existing results, we discuss some particular cases. Finally, numerical illustration along with graphical studies are presented to visualise the effect of the parameters of the system.
Keywords: general bulk service; overloading service; breakdown and repair; closedown; multiple vacations; variant arrival rate.
Enhancing reliability/availability in asset management with retrofitting: a wind turbine case study
by Suna Cinar, Ferenc Szidarovszky, Mehmet Bayram Yildirim
Abstract: In this study, a mixed-integer linear programming (MILP) modelling approach is proposed to identify the optimum maintenance or retrofitting schedule under budget and energy production constraint(s) by improving failure rate of assets. The proposed reliability/availability asset management with retrofitting (RAAMWR) model seeks to maximise the total net profit subject to achieving a target reliability/availability value and minimise the total improvement cost subject to a budgetary constraint. We apply our model to a case study involving wind turbines (WTs). The results of this study show that to reach the target reliability value with improved failure rate data, model selects retrofitting due to lower loss time and high energy production rate of retrofitting options. This optimal retrofitting choice is not only due to low loss time, but also improving the existing failure rate of an asset to reach the target reliability. In addition, the effects of key parameters on total cost, such as operation and maintenance (O&M) cost, retrofitting cost, budget allocated for retrofitting, and different target reliability values on the optimal improvement policy were considered.
Keywords: mixed-integer linear programming; MILP; wind turbine; reliability; asset management; availability; retrofitting; optimisation.