Multi-Period Configuration of Forward and Reverse Integrated Supply Chain Networks with the Choice of Transport Mode

Abstract

In today's competitive business, buying and returning products have become a common practice because of incompleteness of the products or the failure to meet the customer's satisfaction or reusing products. Before handling this cycle, companies need a proper logistics network because of its impact on the e ciency and responsiveness of the supply chain. In this research, a forward and reverse logistics network was proposed for product distribution and collection. The contribution of this paper is a multiperiod, multi-echelon integrated forward and reverse supply chain network design problem with transportation mode selection. Di erent decisions including determination of the optimum number and locations of facilities, facilities' opening time, and transportation mode selection were considered in this paper. Due to the multi-period nature of the problem, the problem is exible for future periods. A mixed integer nonlinear programming model was proposed for the introduced problem, considering di erent levels of facility capacities. As another contribution, a genetic algorithm was developed to cope with the problem's complexity, especially for large-sized instances. E ectiveness and reliability of the algorithm, evaluated by solving several random instances with the obtained numerical results and comparisons, con rmed the capability of the proposed algorithm to nd good solutions within an acceptable processing time period.

Coordinating a closed-loop green supply chain for remanufactured product under competition

“…whereas reverse logistics embraces all those activities which are needed for closing the loop viz. used products recovery, inspection, sorting, remanufacturing, remarketing, and reselling (Guide and Van Wassenhove [2], Eydi et al [3]). According to Ginsburg [4], remanufacturing of end-of-life products can reduce the manufacturing costs by up to 40-65%.…”

Designing a new multi-echelon multi-period closed-loop supply chain network by forecasting demand using time series model: a genetic algorithm

“…Eydi et al (2020) proposed a multi-period multi-echelon forward and reverse supply chain network for product distribution and collection with transportation mode selection. In addition, they formulated a new mixed-integer nonlinear programming model for their problem based on different levels of facility capacities with the maximum profit objective function.…”