Application of Genetic Algorithm on Remanufacturing Reverse Logistics Network Model

Abstract

For the goal of energy-saving and environmental protection and increasing the re-utilization of recycling products for enterprises, the paper discusses an open-loop remanufacturing reverse logistics network which has a location selection of two layers, then constructs a mixed integer linear programming model to achieve the overall minimum cost including the freight between nodes, the fixed cost, the disposal cost and operation cost of storage and demolition nodes and remanufacturing centers, the penalty cost of the unmet or remaining demand quantity, as well as the operating subsidy of recycling product from government for dealing with environmental protection. According to the characteristics of the model, the paper uses two ways to solve the problem which are Lingo and adaptive genetic algorithm based on Matlab, and then provides an instance where solution steps and results analysis are given, which verifies the feasibility of applying adaptive genetic algorithm on the reverse logistics network model.