International Journal of Operational Research (123 papers in press)
Location-Allocation Models for Healthcare Facilities with Long Term Demand
by Ruilin Ouyang, Tasnim Ibn Faiz, Md. Noor-E-Alam
Abstract: Facility location decisions are long term commitments that manufacturing and service industries require to make in accordance with their vision statement, competitive strategies, and with the provisions for future uncertainty. Such decisions involve huge investments, and once the decisions have been executed, recourse options are very costly. Healthcare facility location and allocation decisions are of great importance due to their impact on accessibility to healthcare as well as direct and social cost of peoples well-being in a region. Healthcare facility location decisions that are optimal for current demand may become sub-optimal as demand distribution changes due to population growth and rapid urbanization. Therefore, future demand realizations should be incorporated in the decision making process to ensure long term optimality. The current study presents three mathematical models following grid-based location problem approach and take into account current and future demands in the decision making process. The decisions from the models are optimal long term healthcare facility location and patient allocation decisions for the current time and for a future time point. The first model provides the optimal locations for multiple types of facilities to be built at present and at the future time point and the corresponding allocations of patients to the nearest facilities. In the second model, instead of restricting patient allocation to the nearest facility, a relaxed allocation policy is considered where patients can go to facilities within allowable travel distance. The third model follows more relaxed allocation policy by allowing allocation of patients from one location to multiple facilities. Integer allocation variables are introduced and binary variables are discarded. Finally, the models are implemented with a standard modeling language AMPL and numerical instances were solved with CPLEX solver. Results show that all the models are capable of solving small to medium size problems. In terms of solution quality and computational time, the third model was found to be more suitable than the other two. The long term decision making approach presented in this study can be of great value for government and other organizations in making optimal decisions regarding healthcare or other service facilities.
Keywords: Healthcare facility location; Grid-based location problem; Long term location decision; Integer programming.
Improving recommendation quality by identifying more similar neighbours in a collaborative filtering mechanism
by Rahul Kumar, Pradip Bala, Shubhadeep Mukherjee
Abstract: Recommender systems (RS) act as an information filtering technology to ease the decision-making process of online consumers. Of all the known recommendation techniques, collaborative filtering (CF) remains the most popular. CF mechanism is based on the principle of word-of-mouth communication between like-minded users who share similar historical rating preferences for a common set of items. Traditionally, only those like-minded or similar users of the given user are selected as neighbours who have rated the item under consideration. Resultantly, the similarity strength of neighbours deteriorates as the most similar users may not have rated that item. This paper proposes a new approach for neighbourhood formation by selecting more similar neighbours who have not necessarily rated the item under consideration. Owing to data sparsity, most of the selected neighbours have missing ratings which are predicted using a unique algorithm adopting item based regression. The efficacy of the proposed approach remains superior over existing methods.
Keywords: collaborative filtering; recommender systems; similarity coefficient; true neighbours; prediction algorithm.
Best A* Discovery For Multi Agents Planning
by Mohammed Chennoufi, Fatima Bendella, Maroua Bouzid
Abstract: This paper proposes a new approach for multi-agent planning and decision support. The conventional algorithms such as Dijkstra, A* cannot solve complex problems with spatio-temporal constraints. So we are interested in developing a new strategy for the best path based on BDI agents for an emergency evacuation problem of a population crowd, besides the study of the macroscopic behavior emerging from simple interactions between agents by decreasing the evacuation time which is a challenge and a very complex task. Multi-agent systems are well suited to modeling such systems. The idea is to make a two-dimensional modeling of the environment as a Quadtree graph and an hybrid architecture: A* search from the node, where the individual is located to direct it to the best exit node while adding physiological factors to this search, a robust method for collision avoidance and decision support to help the agent will replace the initial destination with anew one. Our model is implemented and tested with java and Netlogo 5.2.1 platform.
Keywords: Complex System; A*; Multi-agent systems; Crowd; Path; Decision Support; Planning; Evacuation; Simulation; Emergence.
Evaluation of Ethanol Multimodal Transport Logistics: A Case in Brazil
by Henrique Correa, Peter Wanke, Andre Martins
Abstract: This paper evaluates a large-scale ethanol multi-modal logistics system in Brazil. This system mainly involves ethanol logistics activities using pipelines and waterways to supply the Brazilian internal and export markets. A transshipment model is used for the treatment of logistic flows. A linear programming model was developed to determine the transshipment and replenishment flows from more than 400 ethanol plants to more than 70 terminals and distribution centers using various modes of transportation. Optimal results occur when pipeline and waterway systems reach full capacity by taking volume away from road transportation on long distances, suggesting that the use of these options has the potential to make the ethanol logistics in Brazil more efficient and competitive in the future.
Keywords: Ethanol; Transshipment; Pipeline; Waterways; Linear Programming.
A reverse logistics model for decaying items with variable production and remanufacturing incorporating learning effects
by Swati Sharma, S.R. Singh, Mohit Kumar
Abstract: In order to meet environmental concerns/regulations, suppliers often endeavor to recover the residual value of their used products through remanufacturing. In this research article, an integrated production and remanufacturing inventory model for a single supplier and a single buyer is presented. There is one production and one remanufacturing cycle for the supplier while multiple batches are considered for the buyer. Demand rate for the supplier and buyer is taken a linearly increasing function of time. It is presumed that production, remanufacturing and returned rates are demand dependent and items deteriorate while they are kept in storage. This model also incorporates the effect of learning in ordering cost, holding cost, deteriorating cost and purchasing cost for the buyer as these costs reduce cycle by cycle due to learning effect from the previous cycle. The numerical examples, sensitively analysis and graphical illustrations are given to illustrate the model.
Keywords: reverse logistics; inventory model; deterioration; variable production and remanufacturing; learning effects.
Heuristics for disassembly lot sizing problem with lost sales
by Mustapha HROUGA
Abstract: Disassembly is a major activity performed in treatment and recovery facilities and is the most important precedence of product and recovery part. It is defined as a systematic method of separating a product into its constituent parts and subassemblies. As economic activities and environmental pressures increase, the volume of product reverse flows are more and more important and costly. This paper focus on single-item disassembly lot sizing problem without and with lost sales, we propose an optimization approach to minimize the set-up costs and inventory costs in a first time and in second time we include lost sales costs. Compared to classical lot sizing problems with lost sales on a finite planning horizon, our problem has some specificities that require original optimization methods. To this end, we propose three most well-known heuristic approaches for the single-item disassembly lot sizing problem without and with lost sales: Silver Meal (SM), Part Period Balalncing (PPB) and Least Unit Cost (LUC). All three heuristics are myopic in the sense that they only consider the costs between two set-ups periods focus solely on the next demand and ignore costs associated with future demand and have outstanding results for classical lot sizing problem with returns which made then more easy to implement. The performance of the proposed solutions is compared with those obtained from a mathematical programming solver for small instances using different demands configurations (increasing, decreasing and variables) and planning horizon (10, 20 and 30 periods). Results show that the three heuristics used in the classical lot sizing problem can be also used to solve the disassembly lot sizing problem without and with lost sales, especially for small and medium instances. Results also show that: a) SM and PPB outperform LUC, b) increased variation in the demand quantity can lead to reduced cost, showing that certainty is more important than variation of the demands, and c) comparison between proposed heuristics and CPLEX, as an exact solution for small and medium size problems (since there is no effective dynamic programming method for the problem with lost sales), shows that we can trust the proposed heuristics as a solution methodology to solve disassembly lost sizing without and with lost sales for larger instances and more complex problems such as multi-level or capacitated disassembly lot sizing.
Keywords: Disassembly planning; lot-sizing; reverse logistics; lost sales.
Application of a genetic algorithm for multi-item inventory lot-sizing with supplier selection under quantity discount and lead time
by Sunan Klinmalee, Chirawat Woarawichai, Thanakorn Naenna
Abstract: This study presents an application of genetic algorithm (GA) for solving the multi-item inventory lot-sizing problem with supplier selection under discounts and lead time constraints. A mixed-integer linear programming (MILP) model is developed for proposed problem. To solve the problem, a genetic algorithm (GA) with two additional operations is proposed for handling the effect of the problem size. An adaptor for adjusting a chromosome data before the evaluation process and a penalty step for deterring an infeasible solution are developed. Finally, numerical examples are generated to evaluate the performance of the proposed GA, and the comparison with MILP approach about the solution quality and time is presented.
Keywords: genetic algorithm; inventory lot-sizing; supplier selection; lead time; quantity discount; mixed-integer programming.
Hybrid BBO PSO based Extreme Learning Machine Neural Network Model for Mitigation of harmonic distortions in Micro Grids
by Gunasekaran Subramanian, Maheswar Rajagopal
Abstract: Microgrid tends to be the cluster of some of the renewable energy sources like photovoltaic, wind, diesel engine, fuel cell and so on. The most important research area in the power distribution system side is the improvement in the quality of power delivered to the end users. This paper focuses on enhancing the power quality of the microgrid system at the distribution point. Here, in order to improve and deliver quality power, shunt active power filter is employed at the distribution side and the main aim of this paper is to design an appropriate controller that achieves a better compensation for the considered shunt active power filter. It is to be noted that the compensation methodology is dependent on the regulation process of the DC-link capacitor voltage. Traditionally, this regulation process is carried out employing a closed loop proportional-integral (PI) controller. In this paper, a hybrid Biogeography Based Optimization (BBO) Particle Swarm Optimization (PSO) based Extreme Learning Machine (ELM) neural network model is proposed to design the compensation for the shunt active power filter as well to mitigate the harmonics so that effective power gets delivered through the grid. The proposed Hybrid BBO-PSO based ELM as applied for the considered microgrid system is compared with the other methods available in the literature to prove its validity. Simulation results shows that the proposed hybrid controller achieves better solutions for compensating the shunt active power filter for harmonic mitigation in microgrids than the other methods.
Keywords: Microgrid – Shunt active power filter – Power Quality – Harmonic Mitigation – Biogeography Based Optimization – Particle Swarm Optimization – Extreme Learning Machine Neural Networks.
Interference reduction using Particle Swarm Optimization in MIMO-WCDMA Multicellular Networks
by Mohan N.
Abstract: In this paper, Particle Swarm Optimization (PSO) algorithm based interference reduction is proposed in Multiple Input Multiple Output (MIMO) using wide-band code division multiple access (WCDMA). During transmission MIMO network may get interfered by some interference such as co channel interference and adjacent channel interference. To reduce these interferences many algorithms have been proposed in previous research. Further improve the performance of the MIMO-WCDMA network and reduce the bit error rate (BER) an optimized algorithm is PROPOSED. Simulation results of this paper show that bit error rate (BER) is reduced and also throughput of the network also improved.
Keywords: Particle Swarm Optimization (PSO); Multiple Input Multiple Output (MIMO); WCDMA; BER.
Blocking Probability based Admission Control Technique for QoS Provisioning in WDM networks
by M.R. Senkumar, K. Chitra
Abstract: In this paper, we have proposed a blocking probability based
admission control technique for QoS provisioning on in WDM networks, for
this, we estimate the blocking probability for an arriving connection request.
The probability that there is at least one free wavelength at the specified
book-ahead time that remains idle for the whole connection duration. Next to
this an admission control scheme used in each group for deterministic QoS
provisioning. The admission control scheme has its root from network calculus
which can derive deterministic bounds on throughput and delay rather than
statistical averages. Along with the delay metric, the blocking probability is
also considered as the main constraints for admission control. The scheme
allocates the aggregate token bucket for each class of traffic based on its
Keywords: WDM networks; quality of service; QoS; blocking probability.
A suggested method for solving capacitated location problems under fuzzy environment
by Maged Iskander
Abstract: In this paper, a new approach for solving fuzzy capacitated location problems is proposed. Both the capacity and the demand constraints are considered fuzzy while the objective function is not. The max-min approach is utilized within the proposed method. A membership function is defined for the non-fuzzy objective function to convert it to a fuzzy one. The α-cut is employed for the membership functions. The models which are in the form of mixed zero-one nonlinear programs are transformed to their equivalent linear ones. Four mixed zero-one linear programs are required to be sequentially solved. The solution of the fourth program represents the ultimate optimal solution of the problem. The suggested approach is illustrated by a numerical example.
Keywords: fuzzy programming; fuzzy capacitated location problem; max-min approach; Chang’s linearization approach; mixed zero-one programs.
An Analysis of Korean Bank Performance Using Chance-Constrained Data Envelopment Analysis
by Yong Joo Lee, Seong-Jong Joo, TaeWon Hwang
Abstract: For measuring the performance of firms using data envelopment analysis (DEA), many studies assume that inputs and outputs are deterministic. For example, key indicators for financial institutes such as assets, deposits, number of employees, and profits vary over time. Nonetheless, researchers take snapshots of these numbers and analyze them for performance measurement and benchmarking. Similarly, it is not an exception for the studies with DEA for Korean financial institutes. We allow inputs and/or outputs to be stochastic and analyze the comparative performance of Korean banks. We found that large or top five banks were inconsistent sensitivity on the variability of inputs and/or outputs across models. The contributions of our study include demonstrating DEA analysis using stochastic inputs and outputs for the Korean banks and providing realistic insights to the managers of the banks.
Keywords: Performance measurement; benchmarking; data envelopment analysis; stochastic variables; Korean banks; chance constrained DEA.
ABC Algorithm for Estimation of Dynamic Parameters in Radial Power System Transfer path
by Jeha J., S. Charles Raja
Abstract: In the paper, an efficient technique is utilized for improving the dynamic performance of interconnected power system. Here, the artificial bee colony algorithm (ABC) is used to predict the stability of the power system and is evaluated the aggregated machine reactance and inertias in the transfer path. The proposed method is used for estimating the dynamic parameters of the aggregated machines for each area utilizing the amplitudes of voltage oscillations measured at any three intermediate points on the transfer path. The two-machine reduced model is used to represent the inter area dynamics of a radial, two-area power system with intermediate dynamic voltage control. Two types of voltage control equipment are considered, namely, a static Var compensator (SVC), and a Thyristor Controlled Series Capacitor (TCSC). The proposed method focuses on transfer path which is utilized the TCSC for including the purpose of voltage support and reducing the disturbance in the system. Here, the proposed methods employ bus voltage phasor data at several buses including the voltage control bus, and the line currents on the power transfer path. Here, the three phase fault is applied in the power system. Based on the estimation, the dynamics of the power system is improved and the proposed strategy is utilized for improving the overall dynamic security. The proposed technique is implemented in MATLAB/Simulink working platform and the output performance is evaluated & compared with the existing methods such as without facts devices, SVC based controller and (Genetic Algorithm) GA based TCSC controller respectively.
Keywords: Dynamic parameters; voltage; TCSC; SVC; reactance; inertia; ABC and GA.
A continuous review policy based on the Stock Diffusion Theory: Analysis and insights via Monte-Carlo simulation
by Francesco Zammori
Abstract: The Stock Diffusion Theory (SDT) is an innovative model for inventory management, which can be effectively applied even in case of heteroscedastic demand, evolving both in mean and variance. To operate, the SDT requires, as input, the trend of the mean μ(t) and that of the variance σ^2 (t) of the demand. Yet, estimating these functions may be challenging and so our goal is to assess the applicability of the SDT at the operational level. To this aim, we used the SDT to formulate a continuous review policy, characterized by a dynamic reorder level and, next, we introduced two practical ways to estimate μ(t) and σ^2 (t). Lastly, numerical Monte-Carlo simulations were used to assess the performances of the model, with respect to standard continuous review policies taken as benchmark. Obtained outcomes confirm the superiority of the SDT and its applicability in most practical cases.
Keywords: Continuous review policy; Inventory management; Monte-Carlo Simulation; Stock Diffusion Theory.
Adaptive Technique for Transient Stability Constraints Optimal Power Flow
by V. Manjula, A. Mahabub Basha
Abstract: This document explains about an adaptive method for optimal power flow (OPF) of the power system, which is depending on the transient constancy restraints. The adaptive method is the mixture of both Cuckoo Search (CS) algorithm and Artificial Neural Network (ANN). The innovative anticipated adaptive method is extremely flexible in nonlinear loads, suitable for user interface and logical reasoning, and allowing controlling formats. In the predefined generator, the CS algorithm optimizes the generator arrangements by the load demand. The foremost intention of the CS algorithm is to reduce the fuel cost and emission cost. The obtainable ANN method is mainly used to develop the levy flight searching activities of the CS algorithm. The levy flight parameters are generally used to meet of the requirements the ANN, which envisage the precise consequences at the testing time. The anticipated adaptive method is executed in the MATLAB/Simulink platform and the efficiency of the anticipated procedure is investigated by the comparison analysis.
Keywords: Optimal power flow; CS algorithm; Artificial neural networks; Cost minimization; Power loss reduction; Synchronous generator.
Prioritizing Critical Failure Factors for the Adoption of ERP System using TOPSIS Method
by Santosh Kumar Yadav, Dennis Joseph
Abstract: Enterprise resource planning (ERP) applications are complex and difficult to implement. Even after implementation many ERP projects are not used or adopted by employees. Organizations are struggling to convince and motivate employees to adapt smoothly to them. Several personal, managerial and organizational issues contribute to successful adoption. This research paper attempts to identify potential issues that lead to failures in the adoption of ERP systems in enterprises. Earlier studies have identified different contributing issues to the failure of ERP systems. A Questionnaire was developed around these significant influencing issues reported in literature and industry people mostly senior managers having good experience with ERP systems were asked to rate the importance of these factors. TOPSIS method was applied to rank the factors based on their importance in the failure of ERP systems. From the results, it is found that poor top management support and poor quality of testing were the two most important critical failure factors for ERP adoption. While implementing ERP systems, an organization has to give importance to these failure factors based on this rank to ensure ERP implementation success.
Keywords: Enterprise systems; ERP; ERP failure factors; ERP adoption; TOPSIS.
Evaluation and designing reverse logistics for risk-neutral and risk-seeking decision makers
by Aida Nazari Gooran, Hamed Rafiei, Masoud Rabbani
Abstract: Designing appropriate supply chain would provide numerous valuable feedbacks for the whole chain, since using returned products instead of reproducing them, is a more appropriate response to the environmental concerns on the one hand which provides benefit and financial savings for the chains on the other hand. Therefore, this paper presents a three-objective function mathematical model to maximize financial savings and quantities of returned products to the chain and minimize total costs in terms of uncertainty and risk that derives from reverse logistics nature. Finally, the developed model was solved by Monte Carlo simulation and genetic algorithm along with proper risk measures for risk-neutral and risk-seeking decision makers. The results indicated financial savings are one of the best objective functions in order to show superiority of reverse logistics network. As another result, it was pointed out that profitability of the chain increases because of delivering return products before their scrap-life.
Keywords: Reverse logistics; Uncertainty; Risk; Risk measures; Genetic algorithms; Monte Carlo simulation.
Economic ordering policy for deteriorating items with inflation induced time dependent demand under infinite time horizon
by GEETHA KRITHIVASAN, UDAYAKUMAR RAMASAMY
Abstract: This article deals with an Economic Order Quantity (EOQ) model for deteriorating items in which the demand is considered to be inflation induced time dependent under infinite planning horizon. Here, we have considered two different models, that is, shortages are not permitted in model-I and shortages are permitted with partial backlogging in model-II. The salvage value associated with the deteriorated units is also considered. The objective of this work is to minimize the total inventory cost and to find the optimal length of replenishment and the optimal order quantity. Numerical examples given illustrate the solution procedure. Comparative study between the two developed models is carried out. The insights obtained from managerial point of view are discussed in detail with the aid of sensitivity analysis with respect to major parameters of the inventory system.
Keywords: Inventory;Deterioration;Inflation;Salvage value;Shortage;.
Fuzzy Logic Based Multi Level Shunt Active Power Filter for Harmonic Reduction
by Elango Sundaram, Subramanian R, Manikandan V, Ramakrishnan K
Abstract: - In this paper, using a three level diode clamped multilevel inverter and DC capacitor, a shunt active power filter (SAPF) is implemented to mitigate the supply current harmonics and compensate reactive power drawn from nonlinear load. The advantage of using three level inverter paves way to reduced harmonic distortion and switching losses. Fuzzy logic control and unit sine vector control are proposed in this paper for generating reference current for the SAPF. The advantage of fuzzy control is that it is based on a linguistic description and does not require a mathematical model of the system. The implementation of Fuzzy Logic Control (FLC) algorithm is executed using MATLAB fuzzy logic tool box. The proposed pulse width modulation (PWM) method produces the switching signals to the inverter from the sampled reference phase voltage magnitudes as in the case of conventional space vector PWM (SVPWM). The simulation results illustrate that the proposed three level SAPF with low harmonic content in supply current and in phase with the line voltage. The simulation results are validated with prototype model for demonstrating the effectiveness of the system.
Keywords: Fuzzy logic; active filters; total harmonic distortion; pulse width modulation; reactive power.
Constrained Project Scheduling Problem: A Survey of Recent Investigations
by Mohamed Abdelbaset, Asmaa Atef, Abdelnasser Hussien
Abstract: Scheduling and managing projects are very important topics in project management science. Constrained resources project scheduling problem CRPSP is a problem of the purpose of allocating the available resources to specific tasks or activities for achieving specific objectives or purposes such as minimizing the makespan or time of the projects, minimizing the execution cost of the project, or any other specific objective or more than one objective at the same time (multi-objectives resource constrained project scheduling problems). Optimizing constrained resources project scheduling CRPSP is considered as a problem structure of deterministic nature. This structure case is an extension to the critical path method and with the resource usability constraints. Seeking for constrained resource scheduling procedures and scenarios is a very good researched domain considering that finding feasible scheduling plan or procedure under uncertainty conditions has been considered as a hot area for the recent research years and are of harm needs for the researchers' interest. This paper introduces a survey for procedure scenarios, techniques, and models that are considered the main context history of CRPSP and Multi-Mode Constrained Resource project scheduling problems MMCRPSP and classified based on research work principles itself. It aims to exhibits, highlights, and update the recent CRPSP surveys. The current state of art for recent researches is evaluated and the potential research directions and orientations are pointed. Also a new framework is proposed for the researchers of interest for this domain of research.
Keywords: Constrained Resources Project Scheduling Problem - Multi-Mode Constrained Resource Projects – Exact methods – Heuristic methods – Meta-heuristic methods.
High-level Stochastic Project Cost and Duration Planning Methodology Integrating Earned Duration, Schedule and Value, Criticality, Cruciality and Downside Risk Metrics
by David A. Wood
Abstract: A high-level methodology is described to integrate deterministic and stochastic calculations of project networks with parallel pathways of work items. It provides the systematic integration of earned value, earned schedule and earned duration metrics and derivative to-completion forecasts of project cost and duration with stochastically-derived quantitative measures of criticality, cruciality, uncertainty and downside risk measures at project, work item and budget levels. A project network consisting of up to about fifty high-level project work items (rather than hundreds of activities) is evaluated applying critical path analysis using a matrix template that derives the fraction of the project completed at regular intervals (e.g. 2% to 5%) along a baseline planned project schedule the work-progress-breakdown diagram. This matrix is evaluated for each deterministic and stochastic case providing the key information to derive a spectrum earned value metrics, and to quantify uncertainty, down-side risk and criticality at the work-item, pathway and project levels.
Keywords: project cost duration simulation; stochastic earned value duration metrics; probabilistic project network critical path; duration performance index DPI; project versus work-item criticality cruciality; quantified project risk uncertainty; project work-progress-breakdown diagrams.
Sustainable Partner Selection: An Integrated AHP-TOPSIS Approach
by Ramanjan Bhattacharya, Rakesh Raut, Bhaskar. Gardas, Sachin Kamble
Abstract: The selection of an efficient partner for any organization improves its overall performance. In the present research for the selection of an efficient, sustainable partner forty-nine selection criteria were identified through the exhaustive literature review, and by applying the Delphi technique, the evaluation criteria was reduced to sixteen. Later, analytic hierarchy process (AHP) was employed for calculating the relative weights of the shortlisting criteria. Then, the technique for order preference by similarity to ideal solution (TOPSIS) methodology was used for ranking the partners. The findings of the AHP approach revealed that cost (includes environmental cost)/price (C8), environmental competencies (concern for environment) (C15), and human resource management and human rights issues (C9) are the top three significant selection criteria and the results of TOPSIS highlighted that partner B is the best partner amongst the three identified partners. The developed model is intended to guide the decision and policy makers in the identification of the significance or importance of selection criteria, and for formulating the strategies or policies for the selection of efficient partners.
Keywords: partner selection; multi-criteria decision making (MCDM); AHP; TOPSIS; textile industry.
Managing unreliability in automotive supply networks an extension of the joint economic lot size model
by Tim Gruchmann, Marcus Brandenburg
Abstract: Within assembly network supply chains, supply disruptions can occur on every supplier-buyer link. Managing this network unreliability can help to reduce schedule instability and increases the overall efficiency of the supply chain accordingly. In this line, a stylised assembly network supply chain model is proposed with two suppliers and a single buyer using the joint economic lot sizing approach. This supply network can be disrupted by a shortage occurring at one of the two suppliers due to random machine breakdowns, which consequently creates dependent requirements variations affecting both the buyer and the entire network. First, the basic joint economic lot sizing model is extended by the said schedule instability. Second, a solution approach is presented concerning the determination of optimal lot sizes, the investment into the reliability of the supply network as well as the determination of safety stocks. Furthermore, the sensitivity of relevant model parameters is investigated by means of a numerical example. Managerial implications are accordingly derived focusing on the reliability of the supply network members and internal incentive structures.
Keywords: schedule instability; automotive supply networks; joint economic lot sizing; supply unreliability; safety stocks.
A deterministic production inventory model with defective items, imperfect rework process and shortages backordered
by Harun Öztürk
Abstract: The basic assumption of the conventional inventory models is that all items produced are of perfect quality. In practice, some defective items are produced due to process deterioration or other factors. This paper develops a mathematical model for an imperfect production inventory system. It is assumed that the defective items produced in the regular production process consist of scrap, imperfect quality and reworkable items. The rework process is accomplished immediately when the regular production process ends, and the rework process produces scrap, imperfect quality and as-good-as perfect items. A numerical example is provided to illustrate the developed model, and a sensitivity analysis is carried out. It was found that producing scrap and imperfect quality items through the reworking is crucial, since this assumption effects optimal policy. Managerial insights are also presented based on the numerical examples.
Keywords: inventory management; production planning; screening; defective items; imperfect rework process; shortages.
A push strategy optimization model for a marine shrimp farming supply chain network
by Chaimongkol Limpianchob, Masahiro Sasabe, Shoji Kasahara
Abstract: Marine shrimp farming operations in Southeast Asia are still traditional and need to be improved in efficiency. In this paper, we first model a marine shrimp supply chain network, which consists of suppliers, farms, distribution centres, traders, and consumers. We also develop a mixed-integer linear programming under the push strategy framework in order to maximize the farmers profit. Through a sensitivity analysis, we examine how the increase in costs affects the profits. The computational results are presented to demonstrate the feasibility of a real case of smart marine shrimp farming.
Keywords: push strategy; supply chain network; mixed-integer linear programming; marine shrimp farming; giant freshwater prawns.
Cost optimization and maximum entropy analysis of a bulk queueing system with breakdown, controlled arrival and multiple vacations
by Nithya R P, Haridass M
Abstract: This article analyses a single server batch arrival general bulk service queueing system with multiple vacations, controlled arrival of batches and breakdown. The service is done in bulk with a minimum of a customers and a maximum of b customers. The server is assigned for secondary jobs (vacations) repeatedly when the number of customers is inadequate to process. However, all arrivals are not considered for service at all times. During the service period, the arrivals are accepted with a probability α, whereas, during the vacation period, the arrivals are accepted with a probability β. During a batch service, if the server breaks down with probability π, the service for the particular batch is processed without interruption. Upon completion of batch service, the renovation of service station will be considered and during renovation, the arrivals are accepted with probability γ. The probability generating function for the queue size at an arbitrary time epoch, for the proposed queueing model is derived. Various performance measures like expected queue length, expected waiting time, probability that the server is on vacation, probability that the server is busy, expected length of busy and idle period are obtained. A few particular cases are discussed to justify the result obtained. Maximum entropy principle is used to determine the solution for steady state probability distribution of queue size and expected waiting time in the queue. A comparative analysis of the results obtained and the analytical results of the proposed model is carried out. The final analysis is validated through numerical illustration. The cost model is also developed to optimize the cost and analyze the utilization of idle period. The findings of this research demonstrate that, for stochastic modelling of complex queueing systems, maximum entropy principle provides an easy approach to determine the unknown probability distributions subject to the mean value of constraints. Moreover, it is a feasible method which can be readily used in practice for approximating the analytical solution.
Keywords: Bulk arrival; batch service; multiple vacations; breakdown; controlled arrival; maximum entropy principle.
Pricing and cooperative advertising decisions in a two-echelon dual-channel supply chain
by Arash Apornak, ABBAS Keramati
Abstract: Developments of e-commerce lead manufacturers and retailers to open direct online channel versus traditional channel in the market. In this paper we consider a supply chain consisting of a manufacturer and a retailer evaluate the impact of price schemes and cooperative advertising mechanisms on dual-channel supply chain competition in traditional and direct online channels as its setting by using Nash equilibrium and cooperative game then find the optima value of each decision variable of the study under preferred scenarios, According to the results the value of decision variables in traditional channel is more than direct online channel in both scenario and also in profit improvement part the analyses shows both channel is sensitive to demand, The results of this study can help managers to consider the interplay between the upstream and downstream entities of a dual channel.
Keywords: Pricing; Cooperative advertising; Nash Equilibrium; Cooperative game; two echelon supply chain.
Optimization of multi-plant capacitated lot-sizing problems in an integrated supply chain network using calibrated metaheuristic algorithms
by Maryam Mohammadi, Siti Nurmaya Musa, Mohd Bin Omar
Abstract: In this paper, a mathematical model for a multi-item multi-period capacitated lot-sizing problem in an integrated supply chain network composed of multiple suppliers, plants and distribution centers is developed. The combinations of several functions such as purchasing, production, storage, backordering and transportation are considered. The objective is to simultaneously determine the optimal raw material order quantity, production and inventory levels, and the transportation amount, so that the demand can be satisfied with the lowest possible cost. Transfer decisions between plants are made when demand at a plant can be fulfilled by other production sites to cope with the under-capacity and stock-out problems of that plant. Since the proposed model is NP-hard, a genetic algorithm is used to solve the model. To validate the results, particle swarm optimization and imperialist competitive algorithm are applied to solve the model as well. The results show that genetic algorithm offers better solution compared to other algorithms.
Keywords: capacitated lot-sizing; multi-plant; production and distribution planning; integrated supply chain; optimization; metaheuristic algorithms; genetic algorithm; particle swarm optimization; imperialist competitive algorithm.
Location of Depots and Allocation of Buses to Depots in Urban Road Transport Organizations: A Mathematical Model and Greedy Heuristic Algorithm
by M. Mathirajan Mathi, P. Suba, Ramakrishnan Ramanathan
Abstract: Optimizing the cost of operations is one of the major issues in any Urban Road Transport Organizations (URTOs). In this study a decision problem on location of depots (adding new locations and removing existing ones) and allocation of buses to depots is considered. The problem is solved for the case of Bangalore Metropolitan Transport Corporation (BMTC), a major URTO in Karnataka, India. The main focus of this research is to provide analytic methods to minimize the cost of operations comprising (a) dead-kilometre cost, (b) fixed cost associated with introducing new depots, and (c) salvage value due to closing the depots. To do so, a (0-1) mixed Integer Liner Programming (MILP) model is proposed and its workability is demonstrated. In addition to the proposed (0-1) MILP model, a simple greedy heuristic algorithm is also proposed. A computational experiment is developed to understand the performance efficiency of the proposed greedy heuristic algorithm in comparison with the optimal solution. From the average and worst case analyses of the performance evaluation, it is observed that the proposed greedy heuristic algorithm provides near-optimal solution (that is on an average the loss of optimality is less than 0.2 percent). The (0-1) MILP model or the efficient greedy heuristic algorithm proposed in this study can be used to help make better decisions on location of depots and allocation of buses to depots of URTOs in general.
Keywords: Location of Depots; Allocation of Buses to Depots; Dead-Kilometre Costs; Salvage Value; MILP model; Greedy Heuristic Algorithm.
Multi-objective simulation optimisation on discrete sets: a literature review
by Moonyoung Yoon, James Bekker
Abstract: Simulation optimisation is an interesting and fast-growing research field fostered by advances in computer technology and increased computing power. These advances have made it possible to solve complex stochastic optimisation problems using simulation. Most simulation optimisation studies focus on single-objective simulation optimisation (SOSO), and multi-objective simulation optimisation (MOSO) has only recently drawn attention. This paper provides an overview of recent studies on discrete MOSO problems. We surveyed various MOSO algorithms and classified them, based on 1) the size of the feasible solution space, and 2) the method of dealing with the multiple objectives. For the latter, we identified three categories, namely scalarisation methods, the constraint approach, and the Pareto approach. MOSO algorithms in each category are discussed in some detail.rnWe conclude the paper by discussing some related issues in MOSO, which include noise handling techniques and the issue of exploration versus exploitation.rn
Keywords: simulation; optimisation; multi-objective; ranking; selection.
Rotary Heuristic for Uncapacitated Continuous Location-Allocation Problems
by M.D.H. Gamal
Abstract: This paper proposes a constructive heuristic method to solve location-allocation problems. Specifically, we consider the problem of locating m new facilities in a continuous region such that the sum of the weighted distances from the new facilities to n existing facilities is minimized. The distance is measured using the Euclidean-distance metric. This simple technique shows that the solution found is encouraging for the case where the number of users is much larger than the number of facilities to be located.
Keywords: facility location; heuristic; location-allocation.
A modified column generation algorithm for scheduling problem of reentrant hybrid flow shops with queue constraints
by Bing-Hai Zhou, Ke Wang
Abstract: To effectively enhance the production efficiency of multi-reentrant workshop, the queue constraint is taken into account where products are processed layer by layer, and then a scheduling method of reentrant hybrid flow shops based on column generation algorithm is proposed. Firstly, a two-stage scheduling model of reentrant hybrid flow shops is described with parallel machine of single item processing at the first stage and batch processing machine at the second stage and then a mathematical programming model is built with an objective of minimizing the total completion time. A column generation algorithm is developed by decomposing the scheduling problem into main problem and job-level sub-problem. Dynamic programming with multiple decision-making is designed to solve each sub-problem and the newly added column is combined to main problem. Further, the adaptive accelerating strategy is applied to effectively improve the algorithm convergence. In the process of generating integral solutions by using branch-and-bound method, the column pool is built and the neighborhood mutation method is employed. Finally, numerical experiments in different problem scales are carried out to analyze the proposed algorithm. Results verify the validness and feasibility of the proposed algorithm.
Keywords: queue; reentrant; column generation; batch processing; dynamic programming.
Economic Allocation of Farm Land for Commercial Crops-A Case Study in Kasargod Region of India
by Sunith Hebbar, Raveena Suvarna
Abstract: Economic allocation of land, is an important activity in agricultural planning. Due to the changing prices of crops in market, its vital for a farmer to appropriately allocate the land for the various crops to maximize the income. Therefore, this study focus on allocation of land for commercial crops, namely arecanut, pepper, coconut and rubber. Initially, Linear Programming technique was applied to determine the optimum crop mix. The results of which is then compared with the traditional method adopted by the farmer. A sensitivity analysis was then performed to determine the optimal capital requirement. Later on to predict the behaviour of the income on a long run a SD model was developed. The factors like market price, cost of crops and weather conditions on yield were considered. The simulation results predicted that by 2030, the income will rise by 59% than the current condition if the suggested crop-mix is adopted.
Keywords: Commercial crops; Linear Programming Model; Optimization of Crops; System Dynamics.
Multi-Objective Production Planning Problem: A Case Study for Optimal Production
by Ahteshamul Haq, Srikant Gupta, Murshid Kamal, Irfan Ali
Abstract: In this paper, we have formulated a multi-objective production planning model for a hardware firm. This firm produces different types of hardware locks and other items in their production run. The objectives of the firm are to minimize the production cost, minimize the inventory holding cost and maximize the net profit subject to the set of realistic constraints. The production planning problem of a similar type in the past formulated under the certain environment where the input information precisely known to the decision maker (DM). However, in most of the situations, the input information is not precisely known. In such situations, fuzzy set theory plays a vital role in modelling of the problem where the input data has some vagueness.The proposed model of production planning also been formulated under fuzzy environment. Both triangular and trapezoidal fuzzy numbers used to present the vagueness in the input information. The equivalent crisp form of the fuzzy model obtained by two different defuzzification approaches namely ranking function and αcut approach. Henceforth, the formulated models under the certain and fuzzy environment have been solved by the fuzzy goal programming approach.
Keywords: Production Planning Problem; Multi-objective Optimization; Fuzzy Goal Programming; Fuzzy Set Theory.
A hybrid GRASP for solving the bi-objective orienteering problem
by Hasnaa Rezki, Brahim Aghezzaf
Abstract: This paper focuses on the bi-objective orienteering problem (BOOP) that arises in the tourist routes design problem in cities. In this multi-objective extension of the well-known orienteering problem (OP), each point of interest has different profits, which could reflect the multiple preferences of tourists. The aim is to find routes, limited in travel time, that visit some points of interest and provide the maximum of the different total collected profits. In order to determine an effective approximation of the Pareto optimal solutions, we propose a hybrid Greedy Randomized Adaptive Search Procedure (GRASP) in which a General Variable Neighborhood Search (GVNS) is used as an improvement phase. To evaluate the performance of the proposed approach compared to the Pareto Variable Neighborhood Search (P-VNS) technique, we have used the test instances and the results provided by the P-VNS taken from the literature. Computational results reveal that the hybrid GRASP algorithm generates better approximations of Pareto-optimal solutions compared to the P-VNS method.
Keywords: Bi-objective orienteering problem; GRASP; GVNS; Hybrid; Pareto-optimal solutions.
Inventory management policy for perishable products with Weibull deterioration and constrained recovery assumption based on the residual life
by Cinzia Muriana
Abstract: Economic Order Quantity models for perishable products generally disregard the relationship between the deterioration rate and the Characteristic Life (CL). They assume that the cycle time is lower than the CL, and the products that are in stock at the end of the cycle time are considered as outdated. This involves that still fresh products are salvaged at discounted price or disposed of. The paper presents an inventory model for perishable products, namely open dating and fruit and vegetables, in the presence of time-varying CL, Weibull deterioration model, and uncertain demand. The relationship between the Weibull deterioration model and the CL is enforced, determining whether to dispose of the products or salvage them at alternative markets. Results show that the model can be solved and the operating variables optimized.
Keywords: EOQ model; Characteristic Life; Weibull deterioration; open dating foods; fruit and vegetables; Mean Residual Life.
The General Pickup and Delivery Problem with Backtracking Restrictions
by Zachary Bowden, Cliff Ragsdale
Abstract: This paper introduces a model for the General Pickup and Delivery Problem (GPDP) that provides a novel approach to limit the amount of backtracking allowed in the solution. This problem is motivated by the increase in peer-to-peer vehicle transactions via online marketplaces such as eBay and an associated increase in the direct consumer procurement of shipping services for transporting recently purchased vehicles. We approach this problem in the context of a profit seeking objective while considering the cognitive processes and behavioral preferences of the driver as important to the ultimate solution of the routing problem. We offer a method for producing a set of good solutions that are differentiated based on backtracking characteristics of the directional flow of the route.
Keywords: Vehicle routing; backtracking; PDP; profit maximization; behavioral logistics.
Stationary distribution of an infinite-buffer batch-arrival and batch-service queue with random serving capacity and batch-size-dependent service
by Sourav Pradhan, U.C. Gupta
Abstract: In traditional batch-service queueing systems, the mean service time of batches are generally assumed to be constant. However, in numerous applications this assumption may not be appropriate. In telecommunication networks, the transmission rates depend on the number of packets in the batch which can be framed as batch-size-dependent service queue. The objective of this paper is to focus on both queue and server content distribution in an infinite-buffer batch-arrival and batch-service queue with random serving capacity rule and batch-size-dependent service. After deriving a bivariate probability generating function of queue length and server content distribution at departure epoch of a batch, we extract the complete joint distribution in terms of roots of the characteristic equation. We also obtain the system as well as queue length distribution at arbitrary epoch. Finally, a significant number of numerical examples are appended to show the feasibility of the analytic procedure and results where the occurrence of multiple roots have been dealt without facing any difficulty. At the end, a graphical representation of cost of the system shows that batch-size-dependent service is more significant as compared to batch-size-independent service.
Keywords: Batch-arrival; Batch-size-dependent; Random serving capacity; Supplementary variable; Queueing; Joint distribution.
Permutation Flow Shop Scheduling: Variability of Completion Time Differences - NP-Completeness
by Barbara König, Rainer Leisten, Jan Stückrath
Abstract: We consider the permutation flow shop scheduling problem and aim to obtain smoothness of jobs' completion times, by minimizing the variance or the variability of inter-completion times. This problem, including an efficient heuristics, was introduced in (Leisten & Rajendran 2015). Here we solve an open problem from that paper and show that the problem for more than two machines is NP-complete.
Keywords: flow shop scheduling; variability of completion time differences; NP-completeness.
A model for optimal allocation of human resources based on the operational performance of organizational units by multi-agent systems
by Rahim Khanizad, Gholamali Montazer
Abstract: Optimal allocation of human resources is studied in this research. To solve the problem, a model of negotiation between intelligent agents is used in this study. Organizational units are considered as agents that seek for their benefits and use negotiation for human resources and job distribution. We firstly introduce operational performance level to find out how units can guarantee their performance. As a result, in this research, organizational decision making is managed in two levels by agents. In medium level, agents negotiate each other using optimal function to divide human resources optimally. Therefore, the final agreement will be distributed among the organization using the special function developed for this reason. Results have shown that organizational units operational performance is a good criterion for human resources distribution in organization.
Keywords: human resources optimal allocation; intelligent agents; negotiation; optimality; operational performance.
A methodology to surface aspects of organizational culture to facilitate Lean Implementation within SMEs
by ABDULLAH ALKHORAIF, Patrick McLaughlin
Abstract: The purpose of this paper is to provide an instructional guidance on how to surface aspects of Organizational Culture that effect Lean Implementation within small and medium sized manufacturing organization. This paper describe how Grounded theory and Action research can be used inside each other. The paper suggests to not only use a translation method to validate the result but to use also Inter-rate reliability to increase the validity and reduce the subjectivity. The paper also demonstrates how different technique can help management research by including in a time effective way.
Keywords: Lean Implementation (LI)rn Organizational Culture (OC)rn Grounded theoryrnAction researchrn Small and Medium-sized Enterprises (SMEs).
OPTIMIZATION APPROACH TO SOLVE THE TRUCK LOADING AND DELIVERY PROBLEM AT LONG HAUL DISTANCES WITH HETEROGENEOUS PRODUCTS AND FLEET
by Luis-Angel Cantillo, Victor Cantillo, Pablo A. Miranda
Abstract: This paper proposes a sequential optimization approach for addressing a complex real world problem of dispatch planning and freight loading for a set of highly irregular products with a heterogeneous fleet of trucks. The approach focuses on the case of goods with low-density values, highly varied with large travel distances. The propossed approach is based on a two-phase strategy: The first optimizes the space assignment process inside trucks to each type of product. It is achieved by minimizing long-haul transportation costs as a function of the fleet size and capacity, considering a set of predefined feasible and efficient loading solutions or patterns. The second phase minimizes the number of visits per truck, assuming a fleet with fixed size and capacities for each type of product, which is determined in the first stage. The approach was successfully applied to a rolled steel company in Colombia, whose results show that the proposed model efficiently addresses the analyzed problem, which is reflected in reasonable solution times and costs from a practical implementation perspective
Keywords: Truck loading ; Long-haul dispatching ; Heterogeneous fleet ; Irregular shape products ; Multi-commodity ; Big data.
The EOQ Model with Items of Imperfect Quality and Replenishment from Different Suppliers
by Noura Yassine
Abstract: The classical economic order quantity model is extended to the case where the items may be acquired from various suppliers. It is assumed that any lot size received from a supplier contains perfect and imperfect quality items. The percentage of perfect quality items in a lot size is a random variable having a known probability distribution. The imperfect quality items are detected through a 100% screening process conducted at the start of the inventory cycle. When the screening process is concluded, the imperfect quality items are sold in one batch at a discounted price. A mathematical model is developed to determine the total profit function. The optimal order quantity and the proportions of the order acquired from the suppliers are obtained by maximizing the total profit function. An iterative numerical algorithm that determines the optimal solution is proposed. Numerical examples are presented to illustrate the calculations in the case when the percentages of imperfect quality items follow the uniform distribution.
Keywords: Constraint optimization; optimal lot size; probability distribution; imperfect quality items.
Analysis of infinite buffer general bulk service queue with state dependent balking
by Gopal Kumar Gupta, Anuradha Banerjee
Abstract: This paper investigates the effect of impatient phenomena of the arriving customers in a bulk service queue, where inputs are flowing into the system according to the Poisson process and are served in groups according to the `general bulk service' (GBS) rule. On arrival, a customer decides whether to join or balk the system, based on the observation of the system size and status of the server, i.e., whether server is busy or idle. The steady state joint probability distributions of the number of customers in the queue as well as with the server is obtained by using the probability generating function method, which is based on the roots of the characteristic equations formed using probability generating function for steady state joint probabilities. Finally, various performance measures, such as, average queue length, average waiting time, probability that the server is busy, average queue length when server is busy, etc., have been obtained. The paper ends with several numerical discussions to demonstrate the effect of certain model parameters on the key performance measures.
Keywords: Balking; General bulk service rule; Joint probability distribution; Probability generating function; Poisson Queue.
Short-term operating room scheduling: a parallel machine under resource constraints problem
by Mohamed Amine ABDELJAOUED, Zied BAHROUN, Nour El Houda SAADANI
Abstract: The paper tackles the daily scheduling of surgical operations in an operating theatre. The considered operating rooms are identical and the set of operations is subdivided into groups, each of them performed by a single surgeon. The objective is to minimize the ending time of the last completed operation (makespan). We assume that the planning phase, which consists of determining the operations to be scheduled each day and assigning them to surgeons that are available on that day, is already fixed, and we only focus on solving the daily scheduling phase. To the best of our knowledge, few studies specifically focus on very short-term decisions (one-day horizon) in operating room management. The problem is NP-hard and is part of the parallel machine scheduling under resource constraints.
We provide two mathematical models and compare their performance. The first is based on parallel machines scheduling, while the second highlights the similarities with the strip packing problem. Two heuristics based on a dichotomic approach are then introduced. An experimental study comparing their results to optimal solutions, lower bounds and an existing heuristic from the literature shows that the second proposed method performs the best and provides near-optimal or good results for realistic-size instances in reasonable computational times.
Keywords: scheduling; operating room; parallel machines; resource; strip-packing.
Spiral With Line Segment Directory for a Helix Search Path to Find a Randomly Located Target in the Space
by Mohamed El-hadidy
Abstract: In this paper we present more interesting search plan in the space to find a lost hanging black box in the water from a view point of computational stochastic geometry. The space is divided into cubic cells with knowing side length. There exist one searcher moves on Helix path along spiral with line segment directory. Depending on the target has known trivariate known distribution, we focus on the optimal geometry features such as curvature and torsion of the Helix search path which minimize the expected value of detecting the target. Assuming trivariate standard Normal distribution we present numerical example to show the applicability of this model.
Keywords: Computational Stochastic geometry; Search theory; Trivariate standard Normal distribution.
A Comprehensive Review of approaches used for solving Tele-center location allocation problem in geographical plane
by Rajan Gupta, Sunil K. Muttoo, Saibal K. Pal
Abstract: Setup of Tele-center is the world-wide approach for the establishment of Information and communication Technology Infrastructure in rural areas for the overall development of a country. It is a key resource under E-Governance plan in any country, but a major problem with their location allocation is the sustainability. Tele-center establishment require a suitable location to increase the beneficial effect to service seekers. In this research, multi-faceted problems faced by Tele-centers are highlighted. This paper presents a comprehensive study on Tele-centers location allocation problem and all the recent development in multi-facility location problem research area through more than 150 research papers from high ranked peer-reviewed journals. The research survey examines all the important parameters for the facility location problem and an objective function is also formulated for the same. Based on the survey literature, it is found that the new allocation methods based on Meta-heuristic algorithms are emerging. This study would be a useful contribution in the field of location science, Tele-center location allocation and application of Meta-heuristic algorithms in E-Governance.
Keywords: tele-centers; location allocation; common service centers; rural kiosks; meta-heuristic algorithms; e-governance; geographical plane; ICT for Rural region.
Performance analysis of asynchronous priority based Internet router under self-similar traffic input queueing system with Markovian input and hyper-exponential services
by Malla Reddy Perati, Ravi Kumar Gudimalla
Abstract: In this paper, queueing behaviour of asynchronous and priority based Internet router with self-similar traffic input is analyzed. As Markov modulated Poisson process (MMPP) emulates self-similar Internet traffic, it can be used as input process of pertinent queueing system. For quality of service (QoS) guarantee in a Broadband integrated services digital network (B-ISDN), partial buffer sharing (PBS) mechanism is promising one. Since, network traffic is asynchronous and of variable packet lengths, wavelength division multiplexing (WDM) technology is to be employed, according to which, each output port is modelled as multi server queueing system. Moreover, in the modelling, service times (packet lengths) are assumed to follow more general distribution, namely, hyper-exponential (Hk) distribution with k stages in parallel of service. For the said reasons, Internet router here is modelled as MMPP/Hk/s/C queueing system employing PBS mechanism. The performance measures, namely, high priority and low priority packet loss probabilities, and mean lengths of non-critical and critical periods are computed, and presented graphically. This type of analysis is useful in dimensioning the priority based asynchronous router with self-similar traffic input.
Keywords: Internet router; self-similarity; priority packets; partial buffer sharing; multi server queue; hyper-exponential distribution; critical and non-critical periods; loss probability.
On modeling hard combinatorial optimization problems as linear programs: Refutations of the "unconditional impossibility" claims
by Moustapha Diaby, Mark Karwan, Lei Sun
Abstract: There has been a series of developments in the recent literature (by essentially a same "circle" of authors) with the absolute/unconditioned (implicit or explicit) claim that there exists no abstraction of an NP-Complete combinatorial optimization problem in which the defining combinatorial configurations (such as "tours" in the case of the traveling salesman problem (TSP) for example) can be modeled by a polynomial-sized system of linear constraints. The purpose of this paper is to provide general as well as specific refutations for these recent claims.
Keywords: Linear Programming; Combinatorial Optimization; Computational Complexity; Traveling Salesman Problem; TSP; "P vs. NP.".
An Economic Production Quantity Model with Imperfection in Process, Unit Transportation Cost and Backordering
by Mubashir Hayat
Abstract: Determining batch quantity for manufacturer in an imperfect production setup is key issue during the last decade. Several mathematical models have been developed for this purpose but these models are lacking of the consideration of unit transportation cost in the system wide cost. It is quite clear, that nowadays the transportation account for a huge portion of the overall cost of a product. Therefore, there is a need to involve transportation cost into the model for better decision making process. In this way, the paper incorporate unit transportation cost in an imperfect environment and allowing backorders as well as random defects. Three cases have been modelled by assuming the defective rate following uniform, triangular and beta distribution. Sensitivity analysis has been carried out to point out the important specification of all the three cases of the model.
Keywords: EPQ model; Unit transportation cost; Imperfection in process; Backordering.
Evaluation and ranking of the banks and Financial Institutes Using fuzzy AHP and TOPSIS techniques
by Mohammadreza Hasanzadeh, Changiz Valmohammadi
Abstract: The main purpose of this is to evaluate and rank Credit/Financial Institutes of Tehran Stock Market. The criteria were determined based on prior research and securities stock market literature and also based on the factors taken into account in stock selection. After screening the criteria, and through holding interview with experts were eight criteria were finally chosen. Using Fuzzy AHP, relative weights were calculated for each criterion and ultimately based on these weights, banks were ranked using TOPSIS. The results reveal that Bank Pasargad, Karafarin Bank, and Day Bank ranked first, second, and third respectively. One of the major concerns of those companies investing in the securities stock market is identifying the shares or collection of shares that achieve a substantial return in comparison with other companies. Since the group of banks and credit/financial institutes under investigation are among the most renowned and leading agents in Irans capital market, the obtained results could serve as a guidance for investors form one hand and the owners of the survey institutions and banks on the other hand to take necessary measures in accomplishing their objectives. This evaluation and ranking model has significant applied potentials in shares investment of a company among other similar companies in the context of Iran.
Keywords: Securities Stock; Ranking; Multiple Criteria Decision Making (MCDM); Fuzzy Analytic Hierarchical Process (FAHP); TOPSIS; Iran.
Asset management strategies for wind turbines: keeping or retrofitting existing wind turbines?
by Suna Cinar, Saeed Rubaiee, Mehmet Bayram Yildirim
Abstract: In this study, a parallel replacement problem with retrofitting (PRP-R) model is proposed to determine the trade-off between retrofitting and replacing an asset. The primary objective is to identify the replacement, maintenance, and retrofitting schedule that optimise purchasing new assets, operation and maintenance (O&M) cost, and retrofitting cost under budget and production constraints resulting in a mixed-integer linear programming formulation. This model is applied to a case study of energy industry involving wind turbines (WTs). Results show that due to a lower O&M cost, retrofitting is less costly than keeping the WTs. In addition, the effects of key parameters such as O&M cost, retrofitting cost, budget allocated for retrofitting, and governmental subsidy on the optimal replacement policy on total cost are studied. This research contributes a model that can be used to determine if WT retrofitting is economically justified and provides a rigorous analytical framework for optimising the decision-making process over the wind farm life cycle.
Keywords: wind turbine; mixed-integer linear programming; asset management; retrofitting; optimisation.
A Game Theoretic Approach for Integrated Pricing, Lot-Sizing and Advertising Decisions in a Dual-Channel Supply Chain
by Javad Zarei, Morteza Rasti-Barzoki, Seyed Reza Hejazi
Abstract: This paper discusses the coordination of pricing, lot-sizing and advertising policies in a dual-channel supply chain including one manufacturer and one retailer. The manufacturer produces one type of product and sells it to the retailer with wholesale price and, also, directly to consumers through direct channel. Consumers buy the product with retail price from the retailer and with direct sale price from the manufacturer. Demand depends on price and advertising efforts. Decision variables of the manufacturer are the wholesale price, the direct sale price, the amount of national advertising, and the participation rate of the local advertising. Decision variables of the retailer include the retail price, the inventory cycle time and the amount of local advertising. Relationship between the manufacturer and the retailer has been modeled by two non-cooperative games of Nash and Stackelberg-retailer and one cooperative game. Finally, the change effect of the important parameters on the profit functions and the decision variables has been investigated. The results show that with increasing the cross-price sensitivity, the manufacturers equilibrium profit for the two non-cooperative games increases. However, the increase in this parameter has no effect on the retailers equilibrium profit.
Keywords: Supply chain; Pricing; Lot-sizing; Advertising; Game theory.
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.
Inventory model based upon order criticality
by Kamal Sanguri, Sri Vanamalla Venkataraman
Abstract: For a typical distribution network we can segregate the demand at the central demand catering centre as critical if the order is triggered by a direct customer requirement and non-critical if the replenishment order is triggered for routine stocking purpose by the customer touch point. In the traditional model discussed in literature the segregation is based upon the use based criterion, with the objective of keeping the cost of ordering, shortages and inventory at a minimum level. Through this research we propose a modification of the traditional model by incorporating different classes of demand based upon their criticality while maintaining appropriate service levels to them.
Keywords: inventory; rationing; service levels.
Flexible shift scheduling for a call centre using column generation
by Carlos Campos Amezcua, Omar G. Rojas, Emilio Zamudio Gutierrez, Elias Olivares-Benitez
Abstract: A shift scheduling problem for a call centre is solved by applying a column generation method. The objective is to find an employee schedule within the planning horizon that meets staffing requirements provided by the customer and that minimises the costs of excess-staffing and under-staffing. To solve the problem, two iterative models were used: the first being a mixed integer-linear programming model, the master problem, and the second being a column generation model. In a first approach, the master problem was solved considering a fixed number of shift patterns. The second approach was to use both models iteratively to generate shift patterns to be used in the master problem. Both approaches met all constraints relatively fast, but the column generation model decreased the cost considerably when cheaper shift patterns were generated. The models contribute to the current literature by providing flexibility to consider under-coverage and over-coverage at two levels.
Keywords: shift scheduling; call centre; staffing; mixed integer linear programming; master problem; column generation; shift pattern; flexibility.
Reliability Models of a Series-Parallel System with Replacement at Failure
by Ibrahim Yusuf, Nura Khalil
Abstract: The paper deals with the availability analysis of a series-parallel system consisting of four subsystems: A11, B, C and A12. Subsystem B contains units b11 and b12 arranged in active parallel, subsystem C contains units c11 and g12 arranged in active parallel. The system is exposed to two types of failure. Type I failure is a unit failure called partial failure where the failed unit is replaced with new and identical one while type II is a common cause failure to either subsystem B or C in which the failed subsystem is replaced with new one. Two probabilistic models are discussed. In model I (system without common cause failure), the system has type I failure while in model II (system with common cause failure) the system has both type I and II failure. In both models, the system has three modes: full capacity, reduced capacity and failure mode. Failure and replacement rate were assumed to be exponentially distributed. Through the transition diagram, system of first order linear differential equations were developed and solved to obtain the explicit expressions for steady-state availability. At last, some numerical examples have been taken to clarify the results.
Keywords: Availability; series-parallel; common cause failure.
The Second Purchase Decision under Selling Price-Sensitive Stochastic Demand and Purchasing Price Uncertainty
by Xiangling Hu, Jaideep Motwani
Abstract: It is quite common for a retailer to stock a specific quantity of a product more than once during a certain time period and then sell the product to the customers during the selling season. The retailer also has the option to make a second purchase if there is a potential profit increase on account of the purchase. However, due to the stochastic spot market purchasing price and the selling price dependent random demand, the retailer needs to determine whether a second purchase is necessary and if so what are the corresponding order time, quantity, and selling price in order to maximize the expected profit. In this paper, we develop a reality-adaptable solution algorithm to simplify the solution procedure. We also run simulations to analyze the inventory decisions and profits when a second purchase is possible.
Keywords: Supply chain management; purchasing; pricing; Price Uncertainties; Price-Sensitive Stochastic Demand.
Energy-awareness scheduling of unrelated parallel machine problems with multiple resource constraints
by Bing-Hai Zhou, Jiaying Gu
Abstract: This study proposes a framework to investigate the multiple dimensions of consumer value in the context of mobile marketing, to better understand the factors impacting on mobile consumer perceived value. We primarily conducted a series of interviews based on means-end chain theory and in line with the interviews of 179 WeChat official account subscribers. Then, three-step surveys are taken; after revision and testing, the proposed scale and the final six-dimensional model (MCPV scale) emerged. In addition, another study was conducted to validate the scale model, which takes mobile advertising effectiveness, attitudes towards the official account and loyalty towards the official account as consequences of MCPV. The MCPV scale was found to be both reliable and valid; it had significant influence on mobile advertising effectiveness, and it could serve as a framework for further empirical research in the mobile marketing settings. Lastly, theoretical and practical implications were discussed.
Keywords: multi-objective; energy consumption; resource constraints; artificial immune algorithm.
Bargaining in a closed-loop supply chain with consumer returns
by Yertai Tanai, Emmanuel Dechenaux, Eddy B. Patuwo, Alfred Guiffrida
Abstract: The increasing quality of consumer returns creates substantial economic potential for closed-loop supply chains to extract value from returned goods. In this paper, we focus on the supply chain interaction between a retailer and a third party reverse logistics provider (3PRLP) to process consumer returns under a full refund policy. In the model, the retailer orders processed returns from the 3PRLP in exchange for a fee and then resell the processed returns. We compare an uncoordinated supply chain, in which the retailer makes a take-it-or-leave it offer of a fee to the 3PRLP, to a coordinated supply chain, in which the retailer and the 3PRLP jointly decide on the quantity of processed returns and the fee using Nash bargaining. We show that coordination leads to both a higher quantity processed and a higher fee than in the uncoordinated case. We also derive a set of sensitivity results with respect to important parameters.
Keywords: Closed-loop supply chain; third party reverse logistics providers; supply chain coordination; consumer returns; Nash bargaining.
Analysis of a Variant Working Vacation Queue with Customer Impatience and Server Breakdowns
by Vijaya Laxmi Pikkala
Abstract: This paper analyses an infinite buffer single server variant working vacation queueing model in which the arriving customer may balk and the server is subject to breakdown. The service times during regular busy period and working vacation period, vacation times, breakdown times and repair times are assumed to be exponentially distributed and are mutually independent. In working vacation period, the customer may renege due to impatience. We derive the probability generating function of the steady-state probabilities and obtain the closed form expressions of the system size. In addition, we obtain some performance measures and a total expected profit function per unit time is designed to determine the optimal values at the maximum profit. We employ the particle swarm optimisation method to solve the profit optimisation problem.
Keywords: Queue; Balking; Reneging; Variant Working Vacations; Server breakdowns; PSO.
Efficiency Measurement of Canadian Oil and Gas Companies
by Mohamed Dia, Pawoumodom Matthias Takouda, Amirmohsen Golmohammadi
Abstract: In this study, we perform an efficiency analysis of Canadian oil and gas firms. Using data envelopment analysis, technical, managerial and scale scores from ten samples built from 110 oil and gas companies, listed in Canadian stock exchanges, are computed for the years 2012, 2013, 2014, and 2015. Our analysis, supported by appropriate statistical tests, confirms that the Canadian oil and gas industry exhibited predominantly low overall technical efficiency levels both for each of the years and overall for the four years. We have observed that the main source of inefficiencies was the management of operations. In addition, we have seen consistently that across the samples, a statistically significant relationship exists between the efficiency scores and the size of the companies. Finally, we have observed the existence of a relationship between the efficiency scores and the type of producer (pure oil vs. oil and gas), but we could not reach conclusions on the best performer that was consistent across the samples.
Keywords: Data Envelopment Analysis; Efficiency; Oil and Gas companies; Canada.
A dynamic programming approach for solving the economic lot scheduling problem with batch shipments
by Christoph Glock, Fabian Beck
Abstract: This note investigates the economic lot scheduling problem (ELSP) with batch shipments. It first modifies an existing formulation of the ELSP to account both for the cases of equal-sized and geometrically increasing batch shipments, and it then adapts the popular dynamic programming approach of Bomberger to the new planning situation. In addition, the paper specifies some steps of Bomberger's solution procedure that had been formulated imprecisely in the original publication of the author. The paper compares the solution approach proposed in this note to the popular methods of Hanssmann as well as Haessler and Hogue in a numerical experiment and highlights the influence of the batch shipments on the relative performance of the solution procedures. Our results show that the proposed modification reduces the performance disadvantage of Bomberger's basic period approach, which may be interesting especially for practitioners that are interested in an easy-to-apply procedure for solving the ELSP in practice. Our changes to Bomberger's solution procedure support finding the lowest total cost solution that had not always been obtained in earlier publications.
Keywords: Economic Lot Scheduling Problem; Bombergers method; Basic-Period-Approach; batch shipments; dynamic programming.
NEW MODIFIED RATIO TYPE ESTIMATOR OF POPULATION MEAN USING KNOWN MEDIAN OF STUDY VARIABLE
by Dinesh K. Sharma, S.K. Yadav, S.S. Mishra
Abstract: In this paper, we propose an estimator that utilises the known value of the population median of the study variable under simple random sampling without replacement (SRSWOR). As per requirement and for comparison, we derived the bias and mean squared error (MSE) of the proposed estimator to the first degree of approximation. The optimum values of the characterising constants involved in the proposed estimator were also obtained. The characterising scalar may take different values which results in different values of MSE of proposed estimator; therefore its optimum value was obtained. The least value of MSE of proposed estimator is derived for this optimum value of characterising constant. Efficiency comparison of the proposed estimator has been made with other existing competing estimators of the population mean which makes use of auxiliary information under SRSWOR. Theoretical findings regarding the proposed estimator have been verified through the numerical study. It has been shown through a numerical example that the proposed estimator has the least MSE among other existing competing estimators of the population mean of the study variable.
Keywords: Population median; Auxiliary variable; Bias; Mean Squared Error; Relative efficiency.
A Linear Algorithm for a Minimax Location of a Path-Shaped Facility with a Specific Length in a Weighted Tree Network
by Fatma Elsafty, Abdallah Aboutahoun
Abstract: This paper considers the problem of locating a path-shaped facility of a specific size on a weighted tree network. The criterion for optimality used in this paper is the minimax criterion in which the weighted distance to the farthest vertex from the facility is minimised. The minimax criterion gives acceptable results from the point of view of the fast response for the clients who are located far away from the facility. This location problem usually has applications in computer science, information science, and operations research. An O(n) time algorithm is proposed for finding the optimal location of a path-shaped facility of a bounded length on a weighted tree network, where n is the number of vertices in the tree.
Keywords: Tree network; facility location; minimax criterion; central path.
Developing a new chance constrained modified ERM model to measure performance of repair and maintenance groups of IRALCO
by Mohammad Izadikhah
Abstract: Evaluating the performance of repair and maintenance groups is recognised as a key component of improving the strategic and operational levels. The purpose of this paper is to develop a model to evaluate the maintenance groups of IRALCO. Data envelopment analysis (DEA) is a useful method for measuring performance of repair and maintenance groups. However, in real problem there might be stochastic data. For this purpose, this paper presents a new stochastic modified enhanced Russell measure (ERM) model to measure performance of repair and maintenance groups. An important property of the proposed model is stated and proved as a proposition. A case study demonstrates applicability of our approach.
Keywords: Data envelopment analysis (DEA); Chance-constrained data envelopment analysis; Stochastic DEA; Efficiency; Stochastic data.
Worm Optimization Algorithm to minimize the Makespan for the Two-Machine Scheduling Problem with a Single Server
by JEAN-PAUL ARNAOUT
Abstract: This paper considers the problem of scheduling a given set of jobs on two identical parallel machines. Each job must be processed on one of the machines, and prior to processing, the job is set up on its machine using one server; the latter is shared between the two machines. This problem is known as the two-machine scheduling problem with a single server, and our objective is to minimise the makespan. A worm optimisation algorithm (WO) is introduced for this NP-hard problem, and its performance is compared to ant colony optimisation, simulated annealing, and genetic algorithm, as well as an exact approach. The superiority of WO over the other algorithms is obtained through extensive computational results.
Keywords: Worm Optimization; Parallel Machines; Single Server.
Usage of Pedestrian Bridge among the Urban Commuters in Kuala Lumpur: A Conceptual Analysis and Future Direction
by Siti Norida Wahab, Lay Yan Feng, Koay Wui Lim, Amir Aatieff Amir Hussin
Abstract: Pedestrian bridges are one of the safest crossing facilities, allowing pedestrians to cross the road by diverting away from traffic. However, the usage of pedestrian bridges has not been popular in Malaysia. Dreadful conditions of pedestrian bridges further contribute to the low usage. The main aim of this research is to develop a conceptual model to identify the motivating factors affecting the usage of pedestrian bridges among urban commuters in Kuala Lumpur. Four factors were identified from an extensive review of literature to construct the model namely safety, attitude, facilities and convenience. This study serves valuable information for scholar to further study and analyse topic relating to the use of pedestrian bridges. From the practitioners point of view, this study provides valuable information to policy makers and government authorities to integrate and focus on the most motivating factors that could attract more users into utilising pedestrian bridges.
Keywords: Pedestrian Bridge; Urban Travelling Environment; Urban Commuters; Mobilities.
A new Particle Swarm Optimization variant based experimental verification of an industrial robot trajectory planning
by Mahalakshmi S, A. Arokiasamy
Abstract: A new variant of particle swarm optimisation (PSO), constriction coefficient neighbourhood varying inertia weight varying acceleration coefficients particle swarm optimisation (CNVIWVAC PSO) and a conventional differential evolution (DE) algorithms are proposed in this work to do optimal time mechanical energy trajectory planning for an industrial robotic manipulator (MTAB ARISTO 6XT). Three pick and place operations are considered. Minimisation of travelling time of robot end effector and mechanical energy of the actuators are considered as objective functions. This is to ensure fast execution of the desired operation in a minimum possible spending of mechanical energy. All kinematic and dynamic constraints such as position, velocity, acceleration, jerk and torque bounds are considered to ensure smooth as well as practical trajectory. Two stationary obstacles are considered in the path robot manipulator. A comparative analysis of proposed algorithms (DE and CNVIWVAC PSO) with a point-to-point (PTP) algorithm (own system of the MTAB ARISTO 6XT robot) has been carried out by means of experimental tests. The proposed algorithms have been evaluated and experimentally validated. The results proved that the proposed algorithms are better than the existing system (PTP) of robot.
Keywords: Industrial Robot; MTAB ARISTO 6XT robot; minimum time-energy Trajectory planning; pick and place operation; DE; CNVIWVAC PSO.
AN ANALYSIS AND MODELING OF SELECTED BARRIERS FOR SUSTAINABLE MANUFACTURING SYSTEM USING ISM TECHNIQUE
by Subrata Kumar Patra, Tilak Raj, B.B. Arora
Abstract: Traditional manufacturing is largely focused on economics but are attributable for environmental degradation, ecological imbalance and several other negative connotations. To cope up with these challenges, manufacturers have to adopt manufacturing practices amenable to sustainable manufacturing system (SMS). However, transitioning to SMS is a challenging task because a gamut of complex barriers hinders its successful implementation. Data extracted from the reviewed literatures and aptly complimented by the responses of experts, helped in identifying various barriers that are considered as critical from sustainability viewpoint. A focused group discussion (FGD) group consisting of a few experts from steel industry prepared a questionnaire incorporating these barriers. An analysis using interpretive structural modelling (ISM) reveal that lack of government support towards developing new technologies is the most important barrier towards the attainment of SMS. Insights from this analysis will benefit decision makers in formulating suitable strategies to mitigate the ill-effects of these barriers.
Keywords: traditional manufacturing; barriers; SD; sustainable development; sustainability; SMS; sustainable manufacturing system; ISM; interpretive structural modeling; transitivity.
Modelling the sustainable supply chain management practices in Indian industries: A business model using Fuzzy TOPSIS approach
by K. Mathiyazhagan, Sarthak Ahuja
Abstract: Worldwide customers have awareness for the use of eco-friendly products and rules and regulations imposed by government to move towards the sustainable products creates a pressure impact on the industries. The objectives of this study are to develop model and prioritise major sustainable supply chain management (SSCM) practices in Indian industries with a specific focus towards automobile, textile and food sectors. Considered the 19 SSCM practices from the literature review and discussion with experts. The fuzzy technique of order preference for similarity to ideal solution (TOPSIS) has been used to rank. Results shows that practices ISO 14000 and 14001 certification, value stream mapping and corporate social responsibility have been ranked as the topmost priority while taking decisions to ensure perfect sustainability in supply chains.
Keywords: Sustainable Supply Chain Management (SSCM); Technique of Order Preference for Similarity to Ideal Solution (TOPSIS).
A Review and Classification of Heuristic Algorithms for the Inventory Routing Problem
by Stella Sofianopoulou, Ioannis Mitsopoulos
Abstract: The inventory routing problem (IRP) is an integration of vehicle routing and inventory management problems. In the recent years, it has increasingly drawn the attention of the researchers because of its potentially significant practical value. The IRP is classified as NP-hard problem since it subsumes the vehicle routing problem (VRP). This fact led to the development of many heuristic or metaheuristic approaches, although a small number of exact methods have been introduced recently. Heuristic methods offer the advantage of shorter time scales, i.e., greater computational efficiency, on the expense of course of the accuracy of the results. The immediate trigger for this study is our concern about results validation, which has been debatable in early papers, and only recently a systematic effort to create a set of optimally solved benchmark instances has been made. This article presents the heuristic methods for solving the basic variants of IRP found in the literature, stressing the computational results and the solution verification approach, rather than the methodology of the algorithms. The paper concludes with a discussion on the quality of the performance assessment of the proposed algorithms.
Keywords: Inventory routing problem; heuristic algorithms; literature review; results validation.
An M^[X]/G(a,b)/1 queueing system with unreliable server, stand-by server, restricted arrivals, variant threshold policy for vacations
by Karpagam Viji, Ayyappan G
Abstract: We studied the behavior of an M^[X]/G(a, b)/1 queueing system with unreliable server, stand-by server, restricted admissibility and variant threshold policy for vacations in this paper. The stand-by server is utilised only during main servers repair period. At the moment of main servers busy completion or repair completion, if the number of customers in the queue is less than
Keywords: General bulk service; Breakdown and repair; Stand-by server; Restricted admissibility; Variant threshold policy for vacations.
Fuzzy Expectation-spread-skewness model for Shariah-Compliant Portfolio Optimization
by Imen Ben Abdelwahed, Faouzi Trabelsi
Abstract: It is well known that fuzzy portfolios are very useful for investors who are looking for a path to manage risk when dealing with their long-term investment portfolio. In this paper, we propose a new framework to portfolio selection problem based on fuzzy theory in the context of Islamic finance. In order to measure how much an investor satisfies with his profit, skewness is adopted in addition to the first two moments of the distribution. We formulate a new fuzzy (Shariah-compliant) portfolio optimisation problem, referred as fuzzy expectation-spread-skewness (FESpS) model. We discuss the existence of the optimal solution. Besides, we provide numerical methods to approximate the solution, following in parallel probabilistic and analytical approaches. Some examples of application are also studied. Finally, we compare the followed numerical approaches and we state some financial interpretations.
Keywords: Fuzzy portfolio; skewness; Shariah-compliant portfolio; Fuzzy expectation-spread-skewness (FE ? Sp ? S) model; triangular fuzzy variable; spread; analytical approach; probabilistic approach.
Extreme learning machine based investigation on automated detection of architectural distortion in mammograms
by Malar E, Deepan Chakravarthi P
Abstract: Breast cancer, having its origin from the breast tissue is usually detected by mammographic screening. The early detection of breast cancer reduces the mortality rate. A subtle type of breast cancer that often leads to misinterpretation by radiologists is architectural distortion. Though the existing computer aided diagnosis systems efficiently and effectively detect the presence of micro-calcification and masses, the diagnosis of architectural distortion lacks a promising method. This project attempts to detect and classify the regions of mammograms having architectural distortion. MIAS and DDSM database images are enrolled in this research work. 350 region of interests (ROIs) of each architectural distortion and normal cases were extracted. They were subjected to a filtering process, followed by contrast enhancement. Application of Gabor filter to the images resulted in orientation differences between the normal and abnormal images. Statistical features extracted from the resulting images were classified using extreme learning machine classifier. The experimental results obtained from extreme learning machine in comparison with support vector machine had an accuracy of 98.49% and 87.21% for MIAS and DDSM respectively. The accuracy of combined database of which is 85.38%.
Keywords: Breast cancer; Architectural distortion; Extreme Learning Machine; Support Vector Machine; Gabor filters.
Fuzzy bi-objective model for hazardous materials routing and scheduling under demand and service time uncertainty
by Kamran Moghaddam, Jalil Kianfar
Abstract: We develop a fuzzy-based bi-objective optimisation model for hazardous materials (hazmat) vehicle routing and scheduling problem with time windows. The task is to find optimal links and routes to maintain a balance between safe and fast distribution of hazmats between origins and destinations through the transport network. We consider unknown probabilities for hazmat incidents along with a game-theoretic demon approach in a link-based model. Using the Nash game theory approach, an integrated routing and scheduling hazmat shipment problem is formulated. Since the formulated problem is a bi-objective model with travel time and population risk objectives, we also propose a solution method based on a hybrid Monte-Carlo simulation and fuzzy goal programming to obtain the set of Pareto optimal solutions. Computational results of a carefully crafted numerical example are also provided to illustrate the effectiveness of the developed mathematical model and the solution method in obtaining Pareto-optimal solutions.
Keywords: Hazardous material; Vehicle routing and scheduling problem with time windows; Fuzzy multi-objective optimization; Fuzzy goal programming.
A Novel Method of Variable Selection in Data Envelopment Analysis with Entropy Measures
by Zhaotong Lian, Qiang Deng, Qi Fu
Abstract: In data envelopment analysis (DEA) modelling applications, analysts typically experience difficulty in choosing variables when the number of variables is greater than the number of decision-making units (DMUs). In this paper, we develop a novel method to facilitate variable selection in DEA using entropy theory to avoid information redundancy. A numerical analysis is provided to compare our method to those of related studies. The results show that our proposed method produces a lower Akaike information criteria (AIC) value than other approaches. By presenting a real-world case, we show that this new method yields useful managerial results.
Keywords: Data envelopment analysis; Variables Selection; Entropy theory; Akaike information criteria (AIC).
Research and Development Project Funding and the Efficiency of Participating Companies - The Case of the Austrian General Program
by Drinko Kurevija
Abstract: This article analyses the performances of the Austrian Research Promotion Agency's (ARPA) general program. There was no significantly positive shift in best practice frontier for projects between 2009 and 2011. There was a significantly positive shift in the improvement of technology and a significantly negative shift in efficiency for the same period. Fama-MacBeth results show, with sales as the independent variable, that employees and R&D expense are significant but not project income. The stochastic frontier analysis reveals that the null hypothesis of no inefficiency effects is rejected. As anticipated and substantiated, by applying the more appropriate parametric approach, the results did not confirm the findings of Naveh (2005), showing a positive association with initial product development and efficiency. As part of their first phase of product development, the findings suggest the presence of inefficiency effects of firms that participated in ARPA's general program.
Keywords: data envelopment analysis; Malmquist index; Fama-MacBeth; stochastic frontier analysis; programs; projects; efficiency.
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.
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.
A Hybrid State Feedback Controller Design for Two Different Dynamic Systems
by ARAVIND PITCHAI VENKATARAMAN, Veeramani V, S.M. Giri Rajkumar
Abstract: This paper deals the application of error recursive reduction computational (ERRC) technique to improve the performance of state feedback (SF) with integral control design. To highlight the performance of the proposed method is tested on second order and third order system. A second order system is framed based on general assumptions and the third order system is a model of the aircraft pitch control system. The proportional and integral control gain values are obtained using Ackermann's method. Results of with and without ERRC in state feedback design are compared. The controller performance was verified in terms of rise time, settling time, overshoot and tolerance limits.
Keywords: ERRC method; state feedback; state space and higher order systems.
A DEA model towards efficiency estimation of biomass energy production of agro-energy districts
by ANNA KALIOROPOULOU, Thomas Bournaris, Vasileios Manos
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; Biomass energy.
Duality of control problems in general Banach spaces
by S. Padhan, Chandal Nahak, P. Behera
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.ny 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.
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.
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, RANGANATHAN 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 queuing 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; Phase type distribution; Retrial queues; Orbital search; Working vacation; Breakdown and Repair.
Enhancing Reliability-Availability In Asset Management With Retrofitting-A Wind Turbine Case Study
by SUNA CINAR, Mehmet Yildirim, Ferenc Szidarovszky
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; wind turbine; asset management; availability; retrofitting; optimization.
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
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.
Bounding Strategies for obtaining a lower bound for N-job and M-machine flowshop scheduling problem with objective of minimizing the total flowtime of jobs
by Shankar Saravana Kumar, Rajendran Chandrasekaran, Rainer Leisten
Abstract: In this paper, bounding strategies for determining a lower bound on the completion time of a job sequenced in each position in the permutation sequence on each machine in permutation flowshop scheduling problem with minimisation of total flowtime of jobs as objective are discussed. Basically, the bounding strategies are machine-based bounding strategies used for determining the lower bound on total flowtime of jobs for all the small-sized and large-sized benchmark flowshop scheduling problem instances proposed by Vallada et al. (2015). The lower bound matrix can be pruned as tightening constraints into the mixed integer linear programming (MILP) model with objective of minimisation of total flowtime of jobs. Since the flowshop scheduling problem with total flowtime objective is difficult, two kinds of linear programming (LP) relaxation methods are used for determining an LP-based lower bound on total flowtime of jobs for some benchmark problem instances proposed by Vallada et al. (2015).
Keywords: scheduling; flowshop; total flowtime of jobs; lower bound.
The Effect of Order Incentives in a Multi-product Dynamic Inventory Model
by Bin Zhou, Hua Zhong, John Wang
Abstract: This paper addresses the challenges in a multi-product inventory system with uncertain demands. As an incentive, free shipping is used by the supplier to stimulate large orders from customer, who reviews and restocks inventory periodically. The model is first established through stochastic dynamic programming and the characteristics of the optimal policies are analysed. As the optimal control policies are found very complex, accurate lower bound approximations and effective heuristic policies are proposed and discussed. Finally, performance of the lower bounds and heuristics is evaluated through extensive numerical studies which also evaluate the effects of key system parameters including service levels and varied costs.
Keywords: Production and inventory management; Multiple products; Stochastic model; Heuristics.
Optimal Multiplicative Generalized Coordinated Search Technique to Find a D-Dimensional Random Walker
by Mohamed El-hadidy, Ajab Alfreedi, Alaa Alzulaibani
Abstract: This paper presents a new interesting search model that minimises the expected value of the total detection cost of the d-dimensional random walk target with maximum probability. This technique is called a generalised coordinated linear search technique with multiple searchers. The target may be in one of d-direction (dimension) inside the space. We study this technique from a probabilistic and optimisation point of view where each direction is considered as a cylinder and it is searched by two searchers. They start the searching process from any point rather than the origin. The targets initial position is a random variable vector have a known probability distribution. We show the existence of a finite search plan by using the analytical methods. To minimise the expected value of the first meeting time between one of the searchers and the target, we should discuss the existence of the optimality conditions for this search plan and then find the optimal search plan.
A numerical example illustrates the effectiveness of this technique.
Keywords: coordinated search technique; optimality conditions; d-dimensional random walk target.
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.
A green closed-loop supply chain network: a bi-objective mixed integer linear programming model
by Hassan Mina, Farhad Salehian, Sobhgol Gholipour, Hassan Lamouchi
Abstract: The increasing level of customer awareness and application of environmental laws by governments, on the one hand, and the increasing number of competitors, on the other hand, has obliged industry owners to include green activities in the design of the supply chain network. Green activities include any type of action that reduces environmental degradation. Hence, this study seeks to develop a bi-objective, mixed integer linear programming (MILP) model for designing a green supply chain network. In the proposed model, the minimisation of costs and detrimental environmental effects are discussed. LP metric method is used to solve the bi-objective model and the proposed model is run by using simulated data in small and medium sizes in GAMS software. Finally, the model sensitivity analysis is measured in order to evaluate the validity and performance of the proposed model by using demand-driven scenarios. The results of this model indicate the effectiveness of the proposed model.
Keywords: Green supply chain management; Closed-loop supply chain network; Mathematical model.
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.
Analysis of unreliable bulk queueing system with overloading service, variant arrival rate, closedown under multiple vacation policy
by Nirmala Marimuthu, Ayyappan G
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 vacation; Variant arrival rate.
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.
Analysis of self service (s,S) inventory with general lead time and positive service time
by Anoop N. Nair, Jacob M.J
Abstract: This paper deals with the analysis of (s, S) inventory with general lead time and positive service time in a self service environment. The time for serving the inventory is considered as the service time. Both the inter arrival times and service times are assumed to be exponential. Unsatisfied demands are lost. The transient and steady state analysis of such an inventory system are carried out. Explicit expressions for the Laplace transforms of the joint probability distributions of the number of demands and inventory size are obtained using supplementary variable technique. Important system characteristics and numerical results are also presented.
Keywords: Inventory; (s,S) inventory policy; Supplementary variable techniques.
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.
The effect of supply chain structure on inventory management: serial or parallel?
by Xiaoming Li, Qidong Cao, Thomas Griffin
Abstract: While the effect of lead time and its variability on the performance of supply chains continues to attract the attention of academicians and practitioners, the current research has been silent on how a topographic structural change of a supply chain simultaneously reduces both mean and variance of lead time. This study provides such an approach to concurrently reduce both mean and variance of lead time by a simple change on the supply chain structure from serial to parallel. We then show that such lead time reduction reduces mean and variance of lead time demand, which reduce cost in inventory management. We finally illustrate how our approach can be applied to more complex supply chains.
Keywords: lead time reduction; inventory management; supply chain management; serial and parallel; structural change.
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
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.
A review of job shop scheduling problems in multi-factories
by Imen Chaouch, Olfa Belkahla Driss, Khaled Ghedira
Abstract: The distributed job shop scheduling problem (DJSP) deals with the assignment of jobs to factories geographically distributed and with determining a good operation schedule of each factory. It is one of the well-known NP-hard combinatorial optimisation problem to solve optimally. In the last two decades, the problem has captured the interest of a number of researchers and therefore various methods have been employed to study this problem. In this paper, we first present an overview of pioneer studies conducted on solving distributed job shop scheduling problems and a classification of the employed techniques is given. Then, depth analysis of the outcome of existing literature is presented.
Keywords: distributed scheduling; job shop; flexible job shop; optimisation method; survey.
Optimal sourcing policies for single and multiple period scenarios
by Shantanu Shankar Bagchi, A.K. Rao
Abstract: Determining the optimum number of suppliers and the optimum quantities to order from each of them is a critical problem for any supply chain. The objective of this paper is to identify the optimal sourcing policy of a retailer for the single and multi-period context when the firm can source its order to multiple suppliers along with a back-up supplier for the emergency situations. The expected total profit is mathematically modelled for single and multi-period scenarios. The optimal sourcing policy is obtained by maximising the expected total profit with respect to the order quantities. Closed form solution is obtained for uniformly distributed demand for both single and multi-period scenarios. It is observed that the multi-period solution is less sensitive compared to the single-period solution. Also it is found that it is optimal for the firm to lessen the amount of supplier diversification in case of planning for multiple periods.
Keywords: sourcing; supplier yield; stochastic model; demand uncertainty; supply uncertainty; optimisation.
Genetic algorithm for quadratic assignment problems: application of Taguchi method for optimisation
by T.G. Pradeepmon, Vinay V. Panicker, R. Sridharan
Abstract: Quadratic assignment problems (QAPs) are the hardest of combinatorial optimisation problems, with some problems of sizes of the order of 30 still remaining unsolved optimally. Solving QAPs with exact optimisation methods is cumbersome and hence, the use of non-conventional optimisation methods is recommended. Genetic algorithm (GA) being one of the most popular evolutionary algorithms is an appropriate choice for solving QAPs. The methods of operations used in GA influence the solution quality and thus, an optimal combination of parameters and operators are required for the efficient implementation of the algorithm. In this paper, the Taguchi's design of experiments method is used to find the best parameter combination and the best performing combination of operations for GA. The GA thus obtained by incorporating the selected parameter values and operators is then used for solving the QAPs taken from the QAP library. For many of the problems, it is found that the results obtained are within one percentage deviation from the best-known solutions.
Keywords: quadratic assignment problem; QAPs; genetic algorithms; Taguchi's design of experiments method; optimisation of operations and parameters.
A hybrid approach of NSGA-II and TOPSIS for minimising vibration and surface roughness in machining process
by N. Zeelanbasha, V. Senthil, G. Mahesh
Abstract: Increasing vibration amplitude during end milling process can seriously affect the life of end mills and reduces surface finish. Spindle and worktable vibration has a significant influence on surface quality of machined components. This paper confronts and investigates the effect of machining and geometrical parameters (spindle speed, feed rate, axial depth of cut, radial depth of cut and radial rake angle) on spindle and worktable vibration in terms of acceleration amplitude and surface roughness. Experiments were conducted on aluminium alloy 6061-T6 with high-speed steel (HSS) end mill cutter based on the central composite design (CCD). Response surface methodology (RSM) was used to develop the predictive models and the adequacy of the models were verified using analysis of variance (ANOVA). Non-dominated sorting of genetic algorithm (NSGA-II) was adopted to solve the multi objective optimisation problem and the optimised results were resulted with a set of Pareto-optimal solutions. The multi criteria decision making method (MCDM) such as technique for order preference by similarity to ideal solution (TOPSIS) and analytical hierarchy process (AHP) were designed to rank the Pareto optimal solutions based on response of closeness coefficient values.
Keywords: aluminium alloy; decision making; end milling; machining; NSGA-II; optimisation; prediction; TOPSIS; vibration; surface roughness.
Routing vehicles through cross-docking facility for third party logistics service providers
by M. Birasnav, S. Kalaivanan, A. Ramesh, Rajendra Tibrewala
Abstract: This study focuses on a specialised vehicle routing problem (VRP) to transport matchboxes from manufacturing companies to retailers through a cross-dock (cross-docking facility) operated by a third party logistics service provider. Three processes (unloading, consolidating, and loading) are carried out at a cross-dock for completely avoiding or keeping inventory for a very short time. The specialised VRP, addressed in this paper, consists of multiple suppliers (each supplier can produce different brands of products for any number of customers) and multiple customers (each customer can receive orders from any number of suppliers). A mixed integer linear programming model has been developed to solve this kind of NP-hard problem. The objective of this model is to minimise total cost incurred in picking up and transporting the matchboxes from the manufacturers to cross-dock, consolidating matchboxes at cross-dock, and in transporting and delivering the matchboxes to the customers. This study also proposes an effective heuristic procedure to solve the same problem and compares the solution obtained using the heuristic procedure to the optimal solution obtained using the exact method. The findings show that the heuristic method, proposed by us, generates near optimum solutions using significantly less computational time than the exact method.
Keywords: vehicle routing; cross-docking; NP-hard; heuristic; logistics service provider; consolidating; multiple suppliers; multiple customers.
Winsorize tree algorithm for handling outlier in classification problem
by Chee Keong Ch'ng, Nor Idayu Mahat
Abstract: Classification and regression tree (CART) has been widely used nowadays for providing users supports in classification and prediction. However, having outlier in database is inevitable and could affect the size and accuracy of the tree. Negligence in handling the outlier could affect the splitting point which yields to bias and inaccurate tree. In this paper, we propose a winsorize tree algorithm for detecting and handling the outlier before calculating gini index measurement in all non-terminal nodes. As such, the constructed tree will grow without the necessity to be pruned. For evaluation, the proposed approach was compared to classical tree and pruned tree. The results obtained from seven real datasets indicate that the proposed winsorize tree performs as good as or even better compare to the other investigated trees.
Keywords: winsorize tree algorithm; gini index; error rate; classification; outlier; classification and regression tree; winsorized tree.
Special Issue on: Advances in Operations Research
A Postponed Inventory System with Modified M Vacation Policy
by Padmavathi I, Sivakumar B
Abstract: In this article, we analyse a postponed inventory system with a single server under modified M vacation policy, where the server can take atmost M inactive mode. We assume the demand process follows a Markovian Arrival Process and (s, S) ordering policy with exponential lead time. During the inactive mode, the server can be idle or go on vacation, which occurs due to the depletion of inventory. In every inactive mode, server avails an inactive idle period first followed by a vacation period. Inactive idle period and vacation period follow independent phase type distribution. The demand that arrives during the server inactive mode enters the pool of infinite size. The server selects a demand one by one on FCFS rule from the pool, as long as the inventory level is greater than the reorder point and inter selection time follows exponential distribution. A quasi birth and death process is formulated to analyse the system and solved by using the matrix-geometric method. We explicit some system performance measures on the steady state and some illustrative examples are discussed numerically.
Keywords: Postponed inventory system; (s; S) ordering policy; modified vacation policy; Matrix-geometric method.
Dynamic Analysis to Set Idle Time between jobs on a Single Machine
by Senthilvel A N, Umamaheswari S, Arumugam C
Abstract: Scheduling problems are common phenomena in everyday life. Ordering of jobs or tasks to satisfy the constraint determines a schedule. The problem considered here is to find the optimal schedule so as to minimize the earliness and tardiness penalties. This paper proposes a technique to insert the idle time as tight as possible while meeting due date. The penalty, through the insertion of the idle time, is minimized on its own upto the point where no further minimization is achieved. The proposed algorithm gives rise to the set of upper and lower bounds on the objective function value of randomly generated problem set. The proposed algorithm partitions the set of jobs into subsets. Each subset can be scheduled in parallel and grouped later. To prove the effectiveness of the algorithm, 400 sets of different sizes ranging from 15 Jobs to 100 Jobs are solved. The proposed method can be used as a benchmark for future approaches in the area of specific due date scheduling.
Keywords: Scheduling Algorithm; Job Sequencing; NP Class; Heuristic approach; Idle Time; Global Optimization.
Self-Adaptive Bee Colony Optimisation Algorithm for the Flexible Job Shop Scheduling Problem
by Malek Alzaqebah, Salwani Abdullah, Rami Malkawi, Sana Jawarneh
Abstract: The bee colony Optimisation (BCO) algorithm is a nature-inspired algorithm that models the natural behaviour of honey bees as they find nectar and share food sources information with other bees in the hive. This paper presents the BCO algorithm for the flexible job-shop scheduling problem (FJSP), in addition, to improve the neighbourhood search in the BCO algorithm we introduce a self-adaptive mechanism to the BCO algorithm (self-adaptive-BCO algorithm) for adaptively selecting the neighbourhood structure to enhance the local intensification capability of the algorithm and to help the algorithm to escape from a local optimum. We carry out extensive computational experiments on three well-known benchmarks for flexible job-shop scheduling. The BCO algorithm is compared with the self-adaptive-BCO algorithm to test the performance of the latter. The results demonstrate that the self-adaptive-BCO algorithm outperforms the BCO algorithm, the proposed approach also outperforms the best-known algorithms in some datasets and it is comparable with these algorithms in other datasets.
Keywords: bee colony Optimisation; flexible job shop; adaptive neighbourhood search strategy.
A FEPQ model of sustainable items with time and stock dependent demand under trade credit policy
by Bijoy Krishna Debnath, Pinki Majumder, Uttam Kumar Bera
Abstract: Now-a-days Sustainable Fuzzy Economic Production Quantity (s-FEPQ) models gets more
highlighted over classical Fuzzy Economic Production Quantity (EPQ) models. In this paper,
we developed a fuzzy inventory model of sustainable items under time dependent quadratic
rate of fuzzy demand and exponential holding cost where shortages are allowed and are fully
backlogged considering obsolescence cost and carbon emission cost. Also the developed model is compared with stock dependent fuzzy demand. The proposed fuzzy inventory model is solved
via Generalized Hukuhara derivative approach. Two different cases are considered by using
Generalized Hukuhara-(i) differentiability and Generalized Hukuhara-(ii) differentiability. For the first time, in this sustainable fuzzy EPQ model, an alternative approach of payment is proposed. After that, the proposed model has been solved by using multi-objective genetic
algorithm. The proposed model and technique are lastly illustrated by providing numerical
examples. Results from two methods are compared and some sensitivity analyses both in
tabular and graphical forms are presented and discussed.
Keywords: Sustainable EPQ model; fully backlogged shortages; carbon emission; trade credit; alternative approach of payment.
Solving industrial multiprocessor task scheduling problems using an improved monkey search algorithm
by MARIAPPAN KADARKARAINADAR MARICHELVAM, MARIAPPAN GEETHA
Abstract: This paper addresses multiprocessor task scheduling in a multistage hybrid flow shop environment which has been proved to be strongly NP-hard. An improved monkey search algorithm (IMSA) is proposed to solve this problem. The objective is to minimize the makespan which is the completion time of all the tasks in the last stage. The proposed algorithm is tested with three types of problems. A real industrial data is first used. Then, random problem instances are generated and finally, the benchmark problems addressed in literature are also considered. In all the three cases, the results are compared with earlier reported algorithms in the literature and the computational results reveal that the proposed algorithm is competent.
Keywords: scheduling; hybrid flow shop; multiprocessor tasks scheduling; NP-hard; monkey search algorithm; makespan.
A Developed Multicriteria Group Decision Making Method Based on
Interval Valued Hesitant Fuzzy Linguistic Term Sets and Mentality Parameter
by Nesrin Halouani
Abstract: Hesitant Fuzzy Linguistic Term Set (HFLTS) can be considered as a very practical tool in addressing decision problems where people are hesitant to provide their linguistic assessments while avoiding the possible loss of information. Therefore, HFLTS enhances the flexibility to get and represent linguistic information.
This paper deals with this kind of decision making problems by proposing the concept of Interval Valued Hesitant Fuzzy Linguistic Term Sets (IVHFLTS) since it can be considered as an extension of both a linguistic term set and an interval-valued hesitant fuzzy set. This new combination deals with both quantitative and qualitative evaluations. By introducing the mentality parameter for IVHFLTS, we develop a multicriteria group decision making model to deal with hesitant fuzzy linguistic information which avoids the possible loss of information. In order to show the applicability and the efficiency of the proposed method, an example for the selection of the best alternative is given as well as the ranking of the alternatives from the best to worst. The promising numerical results prove that this model is available.
Keywords: Multicriteria Group Decision Making; Hesitant Fuzzy Linguistic Term Sets; mentality parameter; valued interval.