A Genetic Algorithm for Reverse Logistics Network Design

With the increased environmental concerns and stringent environmental laws, reverse logistics has received growing attention throughout this decade. Moreover, an enterprise can save a substantial amount of transportation, inventory, and warehousing costs associated with product returns by optimal handling the product returns. We proposed a reverse logistics model based on supply chain in this paper. The model consists of customers, collection centers, repair centers, and plants. The objective of the model is to minimize the operation costs. A genetic algorithm-based heuristic with associated numerical results is presented in order to obtain good solutions. An experimental is done and result shows that the proposed approach has better synthetic performance in both the computation speed and optimality in reverse logistics network design.