Multi-objective optimization of reverse logistics network based on improved particle swarm optimization

Optimizing reverse logistics network is important to the sustainable development of logistics. In this paper, we established a reverse logistics network multi-objective optimization model which fully considered environment effect and the waste recycling factors, such as locations, frequency, quality and quantity. This model can ensure that both the whole cost of network and the negative impact on the environment are minimum. We improved the particle swarm optimization (PSO) by adopting the grouping and the cataclysm theory, and applied the improved PSO to solve the model. It guaranteed the solution is the global optimization. The simulation results show that our proposed method is simpler and more effective than other algorithms.