Optimal Design of Multi-Echelon Reverse Logistics Using Genetic Algorithm

This paper studies how to design the network of reverse logistics, including selection of locations of initial collection points, centralized return centers, and via initial collection points, the best strategy to send the return products to centralized return centers. Considering the fixed cost of initial collection points, this paper sets up a multi objective mixed integer nonlinear programming model, maximizing the revenue of getting return products and minimizing the difference between service cost and fixed cost for initial collection points. According to the complexity of the problem, a genetic algorithm is used to solve the model. At last an example is presented.