Reverse Logistics Network Optimization by Genetic Algorithm

The interest about recovery of used products and materials have been increased. Therefore, reverse logistics network problem will be powerful and get a great potential competition advantage for enterprises in the future. We formulate a mathematical model of remanufacturing system as three-stage logistics network model for minimizing the total of costs to reverse logistics shipping cost and fixed opening cost of the returning centers, disassembly centers and repair centers. For solving this problem, we propose a genetic algorithm (GA) with priority-based encoding method consisting of time period. The usefulness of the proposed model and algorithm was validated by its application to an illustrative example dealing with products returned.