Designing a Reverse Logistics Network Considering Risk Management

摘要

According to the complexity and risk of the reverse logistics, the main objective of this paper is to propose a multistage methodology for designing a reverse logistics network from the risk management perspective. Firstly, we applied fuzzy DEA model to assess the candidate reverse logistics suppliers based on the risk management. Furthermore, we founded a mixed integer programming model by considering the risk measure of every reverse logistics supplier. Lastly, we designed a hybrid genetic algorithm to solve the mixed integer programming model to allocate the reverses logistics needs and select the optimal reverse logistics supplier combination. Moreover, we analyzed a numerical example to illustrate the feasibility of the methodology studied in this paper to consider the risk management. The research will improve the traditional locationallocation model to satisfy the risk environment, and develop the risk management theory in the reverse logistics fields.