A Fuzzy Goal Programming Approach for Solving Multi-Objective Supply Chain Network Problems with Pareto-Distributed Random Variables

Charles, Vincent; Gupta, Srikant; Ali, Irfan

doi:10.1142/s0218488519500259

Cited by 14 publications

(13 citation statements)

References 38 publications

(31 reference statements)

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“…Mahmoodirad et al (2020) reformulated the closed loop SC network design problem as a multi-objective fuzzy mixed integer linear programming problem using the credibility measure of fuzzy constraints, and then solved by several hybrid fuzzy programming. Charles et al (2019) formulated a probabilistic fuzzy SC network problem and solved it with three different approaches. Rabbani and Talebi (2019) proposed bi-objective nonlinear mathematical programming to minimize the present value of total system costs and the geographical inequalities in the location selection.…”

Section: Fuzzy Operations Research Methods In Scmmentioning

confidence: 99%

An Overview of Fuzzy Techniques in Supply Chain Management: Bibliometrics, Methodologies, Applications and Future Directions

Liao

Zavadskas

2021

Technological and Economic Development of Economy

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Every practice in supply chain management (SCM) requires decision making. However, due to the complexity of evaluated objects and the cognitive limitations of individuals, the decision information given by experts is often fuzzy, which may make it difficult to make decisions. In this regard, many scholars applied fuzzy techniques to solve decision making problems in SCM. Although there were review papers about either fuzzy methods or SCM, most of them did not use bibliometrics methods or did not consider fuzzy sets theory-based techniques comprehensively in SCM. In this paper, for the purpose of analyzing the advances of fuzzy techniques in SCM, we review 301 relevant papers from 1998 to 2020. By the analyses in terms of bibliometrics, methodologies and applications, publication trends, popular methods such as fuzzy MCDM methods, and hot applications such as supplier selection, are found. Finally, we propose future directions regarding fuzzy techniques in SCM. It is hoped that this paper would be helpful for scholars and practitioners in the field of fuzzy decision making and SCM.

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Section: Fuzzy Operations Research Methods In Scmmentioning

confidence: 99%

An Overview of Fuzzy Techniques in Supply Chain Management: Bibliometrics, Methodologies, Applications and Future Directions

Liao

Zavadskas

2021

Technological and Economic Development of Economy

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“…Gupta et al [24] formulated an SCN as a bi-level programming model wherein the determination of the optimal order allocation of products is the DM's primary objective, assuming that the products' demands and supply are fuzzy. Charles et al [12] integrated the various stages of SCN and formulated it as a multi-objective optimization model. To obtain the SCN's optimal solution, they used three different approaches: a simple additive GP, weighted GP, and PGP.…”

Section: Mathematical Modelmentioning

confidence: 99%

Significance of multi-objective optimization in logistics problem for multi-product supply chain network under the intuitionistic fuzzy environment

Gupta

Haq

Ali

et al. 2021

Complex Intell. Syst.

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Determining the methods for fulfilling the continuously increasing customer expectations and maintaining competitiveness in the market while limiting controllable expenses is challenging. Our study thus identifies inefficiencies in the supply chain network (SCN). The initial goal is to obtain the best allocation order for products from various sources with different destinations in an optimal manner. This study considers two types of decision-makers (DMs) operating at two separate groups of SCN, that is, a bi-level decision-making process. The first-level DM moves first and determines the amounts of the quantity transported to distributors, and the second-level DM then rationally chooses their amounts. First-level decision-makers (FLDMs) aimed at minimizing the total costs of transportation, while second-level decision-makers (SLDM) attempt to simultaneously minimize the total delivery time of the SCN and balance the allocation order between various sources and destinations. This investigation implements fuzzy goal programming (FGP) to solve the multi-objective of SCN in an intuitionistic fuzzy environment. The FGP concept was used to define the fuzzy goals, build linear and nonlinear membership functions, and achieve the compromise solution. A real-life case study was used to illustrate the proposed work. The obtained result shows the optimal quantities transported from the various sources to the various destinations that could enable managers to detect the optimum quantity of the product when hierarchical decision-making involving two levels. A case study then illustrates the application of the proposed work.

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“…The suggested model is a three-layer model that encompasses different modes of transport, mobility, ambiguity and direct product shipping between the suppliers, manufacturers and retailers. Charles et al (2019) formulated a multi-objective optimization model of SCN order allocation problem intending to minimize total transportation cost and total delivery time of the network. They solved the formulated model by three different approaches to obtain the optimal solution, namely, a simple additive goal programming approach, weighted goal programming approach and pre-emptive goal programming approach.…”

Section: Literature Reviewmentioning

confidence: 99%

“…This paper aimed directly at minimizing the overall SC cost of the system. Ali et al (2019) developed a new mathematical programming model of inventory management by considering conflicting linear fractional objective functions with different types of factors such as holding cost, purchasing price, selling price, demand and ordering cost. Authors developed two separate models of inventory management with linear and non-linear membership functions and solved them using an intuitionistic fuzzy goal programming technique.…”

Section: Literature Reviewmentioning

confidence: 99%

An efficient stochastic programming approach for solving integrated multi-objective transportation and inventory management problem using goodness of fit

Gupta

Chaudhary

Chatterjee

et al. 2021

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PurposeLogistics is the part of the supply chain (SC) that plans, executes and handles forward and reverse movement and storage of products, services and related information, in order to respond to customers' needs effectively and efficiently. The main concern for logistics is to ensure that the correct product is placed at the right time. This paper introduces a linear model of shipping focused on decision-making, which includes configuration of shipping network, choosing of transport means and transfer of individual customer shipments through a particular transport system.Design/methodology/approachIn this study, authors try to address the problem of supply chain network (SCN) where the primary goal is to determine the appropriate order allocation of products from different sources to different destinations. They also seek to minimize total transportation cost and inventory cost by simultaneously determining optimal locations, flows and shipment composition. The formulated problem of getting optimal allocation turns out to be a problem of multi-objective programming, and it is solved by using the max-addition fuzzy goal programming approach, for obtaining optimal order allocation of products. Furthermore, the problem demand and supply parameters have been considered random in nature, and the maximum likelihood estimation approach has been used to assess the unknown probabilistic distribution parameters with a specified probability level (SPL).FindingsA case study has also been applied for examining the effectiveness and applicability of the developed multi-objective model and the proposed solution methods. Results of this study are very relevant for the manufacturing sector in particular, for those facing logistics issues in SCN. It enables researchers and managers to cope with various types of uncertainty and logistics risks associated with SCN.Research limitations/implicationsThe principal contribution of the proposed model is the improved modelling of transportation and inventory, which are affected by different characteristics of SCN. To demonstrate computational information of the suggested methods and proposed model, a case illustration of SCN is provided. Also, environmentalism is increasingly becoming a significant global concern. Hence, the concept proposed could be extended to include environmental aspects as an objective function or constraint.Originality/valueEfficient integration of logistical cost components, such as transportation costs, inventory costs, with mathematical programming models is an important open issue in logistics optimization. This study expands conventional facility location models to incorporate a range of logistic system elements such as transportation cost and different types of inventory cost, in a multi-product, multi-site network. The research is original and is focused on case studies of real life.

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A Fuzzy Goal Programming Approach for Solving Multi-Objective Supply Chain Network Problems with Pareto-Distributed Random Variables

Cited by 14 publications

References 38 publications

An Overview of Fuzzy Techniques in Supply Chain Management: Bibliometrics, Methodologies, Applications and Future Directions

An Overview of Fuzzy Techniques in Supply Chain Management: Bibliometrics, Methodologies, Applications and Future Directions

Significance of multi-objective optimization in logistics problem for multi-product supply chain network under the intuitionistic fuzzy environment

An efficient stochastic programming approach for solving integrated multi-objective transportation and inventory management problem using goodness of fit

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