Benders Decomposition for Supply Chain Network Redesign with Capacity Planning and Multi-Period Pricing

Demand fluctuations, network cost increase, and new services proposition for customers make companies more interesting in network redesigning problems. these problems allow the existing network to increase or decrease its capacity in order to meet changing customers ’ demands. in this study, a linear mixed integer programming model is proposed to redesign a supply chain network which has price-sensitive customers. in addition, due to the nature of the problem, both strategic and tactical decisions are taken into account simultaneously. strategic decisions consist of opening new facilities, closing existing ones, and adding discrete capacity levels to all network facilities. tactical facilities are pricing and determining flow between different network echelons. pricing is an important fragment of supply chain due to two reasons: first, it represents potential revenue of each product; second, based on supply-demand relations, it enables supply chain to provide demands by making suitable changes in number of facilities and their capacities. therefore, this model aims to consider both pricing and redesigning decisions simultaneously in order to maximize the network profit. based on the solution time of designing/redesigning problems with cplex solver in gams, these problems are among the complex and challenging ones. to overcome this problem in this study, benders decomposition approach was used to solve a multi-product, multiechelon and multi-period supply chain network redesigning problem with price-sensitive customers. results prove the appropriate performance of the proposed algorithm for the model.