Research On Closed-loop Supply Chain Problem Based On Genetic Algorithm

With the development of the global business in the 21st century, the areas ofsupply chain management have extended to the usage and the end-of-life stage ofproduct ,which yields the development of the so called closed-loop supply chain .As a result, how to improve the efficiency of the whole closed-loop supply chain hasattracted great attention of enterprises as well as scholars.Based on the analysis of existing study ,this thesis focuses on the networkdesign of closed-loop supply chain .We pay particular attention to the networkdesign of product recovery and the third-party logistics providers.We first study the network design of product returns in a closed-loop supplychain.We establish a mixed integer programming model involving customers, col-lection points ,collection center and service time .We propose a genetic algorithmto solve the problem that minimize the return cost and rationalize the networkstructure of product recovery.We then study the network design of third-party logistics providers.Becausethird-party logistics providers in the management of closed-loop supply chain playa very important role a nonlinear mixed integer programming model involving cus-tomers, mixed distribution centers and plants is introduced and a genetic algorithmis presented to solve it.thus we dynamically integrate the supply chain and enhancethe efficiency of whole closed-loop supply chain.We also do numerical simulations to test the proposed models.The results thatour study is in an accordance with the real situation.