MULTI-ECHELON REVERSE SUPPLY CHAIN NETWORK DESIGN WITH SPECIFIED RETURNS USING PARTICLE SWARM OPTIMIZATION

摘要

This paper focuses on the development of an optimization mathematical model for a reverse supply chain network that contains forward and reverse logistical plans in the multi-echelon system. In the reverse process, the defective products are returned to the original manufacture/supplier (specified returns) to be produced again. The next period covers the quantity of defective products for the present period, as well as the demands for the new period. To solve the mathematical model efficiently, a particle swarm optimization (PSO) solution is proposed, called PSOsm. The PSOsm introduces the saltation mechanism into the procedure of the original PSO to increase the search area, which prevents the solution being laid on the local solution. Finally, to illustrate the performance of the PSOsm, the original PSO and a genetic algorithm (GA) are employed to find the solution for the proposed problem and the performance of both methods is compared. The results show that the PSOsm provides a better solution.