International Journal of Advanced Operations Management (14 papers in press)
A TOPSIS, VIKOR and DEA Integrated Evaluation Method with BELIEF Structure under Uncertainty to Rank Alternatives
by Amir Amini, Alireza Alinezhad, Fahimeh Yazdipoor
Abstract: Across diverse science branches and fields multi-criteria decision making (MCDM) methods have received much attention from researchers and practitioners in evaluating, assessing and ranking alternatives as a sub-discipline and full-grown branch of operations research. This study proposes a combined method, based on a new compromised solution method and data envelopment analysis (DEA) to evaluate the efficiency of decision-making units (DMUs). By using the technique for order of preference by similarity to ideal solution (TOPSIS) and VIKOR method, in the new compromised programming approach two concepts are considered simultaneously. First, the optimal alternative is closer to positive ideal solution (PIS) and farther from negative ideal solution (NIS). Second, the proposed method provides a maximum group utility for the majority and a minimum of an individual regret for the opponent. In this method weight of efficiency witch obtained from new compromised solution method is multiplied by the weight of CCR model of DEA. The problem involves BELIEF parameters in the solution procedure. Thus, the new proposed method that applied the advantages of TOPSIS, VIKOR and DEA and belief structure simultaneously was used as a group decision making problem to exploit many experts judgments. Finally, to illustrate the proposed method, an illustrative example is provided.
Keywords: TOPSIS; VIKOR; DEA; Compromised Solution Method; Belief Structure.
Exploring the relationships between continuous improvement and predictive analytics
by Lanndon Ocampo, Brian Galli
Abstract: This study aimed to examine the elements and applications of Predictive Analytics (PA) models within the field of Continuous Improvement (CI). While the roles of data science, PA, and Big Data have been explored in the current literature (e.g., supply chain management), fragmented insights scarcely exist concerning the role of PA on CI initiatives. Articles concerning the role of PA and BI in CI projects were utilized in a systematic literature review. Furthermore, the paper stresses the vital role that Big Data Analytics plays in both CI and PA during decision-making. The paper studies other important CI and PA aspects that pertain to Continuous Improvement projects, which are aspects that are often overlooked in the existing literature. The findings from this study emphasize the critical role that PA tools and concepts can and should have in CI initiatives. Critical organizational and operational structures also need to be implemented to establish and maintain the use of PA tools and concepts in CI initiatives. Overall, this paper serves to fill the gap that overlooks the relationship between these two variables.
Keywords: Data; Predictive Analytics; Continuous Improvement; Business Intelligence; Big Data.
Time-Cost Trade-off in a Multi index Bi-criteria Fixed Charge Transportation Problem
by Sungeeta Singh, Renu Tuli, Deepali Sarode
Abstract: This paper is motivated by the necessity of finding efficient time-cost trade-off pairs for Multi Index Bi-criteria Fixed Charge Transportation Problem (MIBCFCTP) where the time criteria assumes greater significance than the cost criteria and is therefore minimized first. An algorithm is developed to find the time-cost trade-off pairs for the MIBCFCTP. So far no study on time-cost pairs of MIBCFCTP has been undertaken, a gap which the proposed algorithm aims to fulfil. Results of a numerical illustration are obtained by the proposed algorithm by extended Vogels approximation Method. Although the proposed algorithm follows a completely different approach than the existing methods of finding cost-time trade off pairs for the MIBCFCTP, however both being optimization methods their optimal solutions are comparable and it is observed that the proposed algorithm is a better alternative in MIBCFCTPs if time minimization holds priority over cost minimization.\r\n\r\n
Keywords: Multi Index transportation problem; time-cost trade-off pair; fixed charge.
OPTIMIZING THE FINANCIAL PERFORMANCE OF SUPPLY CHAIN A CASE STUDY
by Saleeshya P.G, Vinayak Rajan, Nigil Premkumar
Abstract: This paper is an outcome of a study carried out in a brake manufacturing company in India. Based on the literature review, field study and industry study, we have identified various enablers of financial supply chain. The objective of this paper is to strengthen the financial supply chain by eliminating the non-value added elements, optimizing the inventory levels and finally reducing the rejection level of poor quality products by ranking them according to their severity of defects. By identifying these factors and forces, an organization can channel its resources in the most effective way in order to enhance the achievement potential of its various performance indicators.Value Stream Mapping has been used to eliminate the non-value added processes and thereby helped the company to reduce the production lead-time.The 0-1 Knapsack methodology enabled us to optimize the value of goods flowing through the processes, with outputs showing a commendable increase in the financial chain of the process. Data Envelopment Analysis provides an insight into what the important indices must be, so that each step in the inspection process carried out is made efficient, thereby minimizing the rejection levels.
Keywords: Supply Chain Management; Financial Supply Chain; Value Stream Mapping; Inventory Analysis; Knapsack Methodology; Data Envelopment Analysis.
The Design of a Knowledge-based System for Quality Management in Healthcare: Case Study
by Yousuf Al Khamisi, Mohammed Khurshid Khan, Edurardu Munive-Hernandez
Abstract: The current healthcare systems have numerous gaps that need to be filled to reach the best practice. Healthcare organizations have used different Quality Management (QM) tools to monitor and control its services.
This paper presents a novel approach to design and validate a hybrid Knowledge-Based System (KBS) to evaluate QM of healthcare Environment (QMHE) using a hybrid system that has not been used before. The proposed system will be combined with Gauge Absence Perquisite (GAP) method to sustain a successful operation of the large number of Key Performance Indicators (KPIs) that involved in QMHE and to detect the gap between each KPI and the anticipated point. Employment of KB system offers the chance to deal with users in an appropriate way and to support in the decision-making process. Moreover, by including instructive features, the KB system can be used as a learning device for quality managers in healthcare organizations. It firstly focuses on the KB components, followed by the GAP methodology and then the application of the KB-QMHE at a tertiary hospital in Oman. Finally, a summary of the complete KB-QMHE outcomes of its application there is shown.
The system will support the healthcare governance to enhance the patient safety culture and QM efficiency. Out of 354 KB rules answered, the system has categorised 225 as GPs and the remaining 128 as BPs. The 128 bad points are categorised into different problem categories (20 PC-1, 34 PC-2, 34 PC-3, 40 PC-4, and 0 PC-5) where they represent the actions that need to be enhanced to reach the desired level of quality management.
Keywords: Knowledge based (KB) – Gauging Absence of Pre-requisite (GAP) - Quality Management in Healthcare (QMHC) - Expert System (ES).
MINIMISING THE MAKESPAN IN OPEN SHOP SCHEDULING PROBLEMS USING VARIANTS OF DISCRETE FIREFLY ALGORITHM
by Hussain Lal, Vishnu K R, A. Noorul Haq
Abstract: Minimising makespan in open shop scheduling problem is the aim of this research work. The scheduling problems consist of n jobs and m machines, in which each job has Ooperations. The processing time for 50 open shop scheduling problems was generated using a linear congruential random number generator. A non-traditional algorithm called Discrete Firefly Algorithm is proposed to minimise the makespan of open shop scheduling problems and this method is referred as A1. Discrete Firefly Algorithm is also hybridized along with other heuristic algorithms in two ways: i). Firefly Algorithm is hybridized with Longest Total Remaining Processing on other Machines and local search algorithms which is referred as A2. ii). Firefly Algorithm is hybridized with Simulated Annealing and referred as A3. Novelty of this work focuses on the application of open shop scheduling problems in quality control of a production industry.
Keywords: Makespan; Discrete Firefly Algorithm; Hybrid Meta-heuristic Algorithms.
A stochastic model of a production-inventory system with consideration of production disruption
by Rubayet Karim, Koichi Nakade
Abstract: In this paper, we develop a stochastic production-inventory model that faces random production disruption. In each fixed time planning horizon, the inventory position is affected by production disruption. The production disruption time and the disruption recovery time in a single planning horizon are stochastic. The process of the inventory levels at the beginning of the time horizon is formulated by using a finite state discrete-time Markov chain. We derive expressions of the transition probability and the long-run average cost. The optimum solution is obtained through numerical experiments. The result shows that under the circumstance of production time constraint, the incorporation of safety stock in a disruption prone production inventory system helps to minimize the long run average cost. Finally, sensitivity analysis has been given to demonstrate the usefulness of the model. This model assists decision makers to not only determine the optimal safety stock quantity but also reveal distinct effect and/or joint impacts of individual cost parameters, disruption probability on the decision regarding selection of safety stock.
Keywords: disruption recovery time; production disruption; production-inventory system; safety stock; optimization.
Special Issue on: Lean, Agile, Resilient and Green Supply Chain Management
Enhancing stock efficiency and environmental sustainability goals in direct distribution logistic networks
by Marco Bortolini, Francesco Gabriele Galizia, Mauro Gamberi, Cristina Mora, Francesco Pilati
Abstract: In modern business, industrial companies embrace lean philosophy to increase their efficiency moving toward the so-called continuous improvement of industrial processes. In parallel, according to the international regulations and stakeholder pressures, rising attention is toward sustainable environmental, i.e., green, practices. A relevant scientific area addresses the topic of matching lean management (LM) and green management (GM) principles within logistics, from a quantitative and optimised perspective. This paper follows this stream and proposes a bi-objective model optimising stock efficiency and environmental sustainability in the design of direct distribution logistic networks. The former goal belongs to LM, the latter belongs to GM. The model application to an Italian case study showcases its benefit reducing the average stock without a relevant increase of the emissions due to frequent replenishments. A cost analysis of the results completes this paper to include the economic dimension within the study boundaries.
Keywords: environmental sustainability; green supply chain; lean thinking; supply chain management; SCM; distribution logistic network design; stock efficiency; bi-objective optimisation.
Exploring ecosystem network analysis to balance resilience and performance in sustainable supply chain design
by Vitor De Souza, Jacqueline Bloemhof-Ruwaard, Milton Borsato
Abstract: Sustainable supply chain design can be performed using optimisation strategies for minimising environmental impacts while maximising profit. It is not clear how such strategies influence the resilience of a supply chain - its ability to handle disturbances without compromising its function. This research used the ecosystem network analysis (ENA) to evaluate the resilience during the design of a sugar beet supply chain. The ε-constraint method was used to solve a multi-objective, mixed integer linear programming (MOMILP) model. Results showed that ENA results are compromised when the strategy of minimising environmental impacts is used, due to the increased fragility of the configuration, compared with the configuration from the profit maximisation strategy. Sensitivity analysis also revealed that, when the number of facilities is increased, ENA results improve while profit is decreased. ENA showed an interesting potential to support the pursuit of balance between resilience and performance during early design stages.
Keywords: resilience; ecosystem network analysis; ENA; sustainable supply chain design; SSCD; multi-objective programming.
Green optimisation for LRP problem using a genetic algorithm and a dynamic island model
by Zineb Benotmane, Ghalem Belalem, Abdelkader Neki
Abstract: It has grown quite conspicuous that no company is immune to the increase in fuel prices and energy sources used for air conditioning, refrigeration and heating, as well as traffic congestion and the degradation of road infrastructures. It is for this reason that companies are increasingly concerned about energy and environmental issues and are, therefore, more aware of the need to revise their logistics for the purpose of reducing costs and increasing competitiveness. In order to minimise the energy costs associated with transportation, it is sensical to consider a two-echelon location routing problem (2E-LRP) where two distribution levels are composed of three disjoint sets of nodes corresponding to the depots, the distribution centres and the customers, respectively. For this, we propose a mathematical model, a genetic algorithm, and a dynamic island model to optimise the assignment and the routing of freight. Eventual results show a minimisation of energy cost and CO2 rate.
Keywords: genetic algorithm; GA; dynamic island model; optimisation; LRP problem; green supply chain; two-echelon transportation; energy cost; CO2 rate; metaheuristic.
Trade-off among lean, agile, resilient and green paradigms: an empirical study on pharmaceutical industry in Jordan using a TOPSIS-entropy method
by Taghrid Suifan, Moutaz Alazab, Salah Alhyari
Abstract: This study proposes an integrated multi-criteria decision analysis method (MCDM) to analyse trade-offs among different supply chain management (SCM) paradigms associated with competitive priorities. The study employs the entropy method to derive the alternative weights of the evaluation criteria. The study also employs the technique for order of preference by similarity to ideal solution (TOPSIS) to rank feasible alternatives in order of preference, and then measure trade-offs among the conflicting objectives. A sensitivity analysis is performed to confirm the robustness of the proposed model. An empirical study approach is used to identify the trade-offs in the pharmaceutical supply chains context. The results indicate that the TOPSIS and entropy methods can be utilised in a multi-decision analysis process in which SCM paradigms should be implemented in order to positively influence the competitive position. The findings also reveal that competitive priorities differ between each paradigm. For the pharmaceutical industry of Jordan, the sequence of competitive priorities that arise from this study is thus: first 'quality' should be developed, then 'know-how', 'flexibility', 'delivery', 'customer focus', 'innovation', and finally, 'cost'. This finding represents that, the competitive priority that is most affected by the SCM paradigms is the 'quality' priority.
Keywords: trade-offs; supply chain management paradigms; entropy weight; TOPSIS method; competitive priorities; Jordan.
Improvement of steel melting operations at a Caribbean company: a lean manufacturing approach
by Boppana V. Chowdary, Christopher Fullerton
Abstract: The purpose of this paper is to examine the effects of deploying lean manufacturing (LM) techniques in a Caribbean steel manufacturing firm. To conduct the study, a comprehensive review of literature was performed. The problems faced by the company were analysed using value stream mapping in conjunction with 5-why and fishbone quality tools. The study shows that the lead time can be reduced by 37%, reduction in processing time by 7.5% and reduction in work-in-process inventory by (71%). Overall, the study not only provides a road map for similar manufacturing companies elsewhere to achieve operational leanness but it is also valuable for academic community to gain insights into the practicality of the proposed LM strategies. However, the research findings are based on a single case study and results have been validated by simulation.
Keywords: Caribbean steel melting; lean manufacturing; LM; 5S; 5-why; value stream mapping; VSM.
The effect of IT integration on improving agility, integration and performance of supply chain
by Reza Samizadeh, Saedeh Aghagoli, Sahar Vatankhah
Abstract: In recent decades, companies have been trying to use various methods and means to meet customer's needs quickly in order to survive in competitive market and gain more profit. To reach this purpose, information technology has acted as an enabler in different parts of the supply chain and companies. Although there is a wide range of researches investigating the role of IT on supply chain performance (SCP), the literature review has had many gaps. The contribution of this work in comparison with previous models is the impact of studies simultaneously: 1) IT integration; 2) agility and integration on the performance which has not studied until now. This study proposed a new conceptual model to analyse the direct and indirect effect of these items on each other. In addition, a discussion about integrity and agility of the supply chain is a new issue in the Iranian market.
Keywords: IT integration; supply chain performance; SCP; agility; integrity.
Which practices are lean, agile and resilient? Literature review and practitioners' perspective
by Maryam Lotfi
Abstract: The need to be lean in terms of cost effectiveness, agile in terms of customer responsiveness and resilient in terms of being aware of risks and becoming ready to encounter them and passing them in the best way possible, is an undeniable issue in the supply chain. While the three concepts seem to overlap, they also have some distinct parts and this causes the confusion presented in both the literature and practice. The purpose is then to clarify the boundaries of the three concepts to reduce this confusion. The research is empirical. Survey data were collected from 185 companies from different industries in Germany. In line with literature, this empirical research shows that there are some practices that purely affect leanness, agility or resilience and there are other practices that affect leanness and agility both, agility and resilience both and finally the three of leanness, agility and resilience.
Keywords: resilience; leanness; agility; supply chain management.