Locating Service Centers to Maximize the Competitive Share in a Closed Supply Chain

Document Type: Research Paper

Authors

Department of Industrial Engineering, Yazd University, Yazd, Iran

Abstract

Competitive location deals with the problem of locating facilities to provide services to the customers, where other competing facilities offer the same services. Many competitive location models are presented in the literature. However, the literature on competitive location considering reverse logistic in closed-loop supply chain is rather scarce. Also, there are two main approaches in the related literature: increasing profit, and increasing market share of the service centers. Most of the studies in the literature consider one of these issues as the objective function. This study shows that these objectives may have conflict with each other. Therefore, addressing these issues simultaneously is important for a successful design of supply chain. This paper addresses a novel biobjective competitive facility location problem in a closed-loop supply chain, so that increasing profit and market share are considered simultaneously. On the other hand, in the real world, the customer may choose facilities that are not necessarily close to them, because of the greater attractiveness of other facilities. Hence, in this study, a new relationship is introduced to establish the attractiveness of each potential center for customers based on the distance and quality of service centers. In order to solve the proposed model and tackle the computational complexity of the proposed model, two approaches are employed: LP-metric and NSGAII. Furthermore, multiple numerical instances are established and solved by employing the exact approach of LP-metric through GAMS. Results are assessed in order to validate the accuracy of the proposed model. The best value of “P” in LP-metric approach is obtained via analyzing the results. Furthermore, the performance of the NSGAII is analyzed by comparing to the exact solution of LP-metric through GAMS. Results indicate that the proposed NSGAII is more appropriate than LP-metric, and thus, solving the large size problems through GAMS in a logical time is impossible.

Keywords

Main Subjects


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