关键词: 多车场车辆路径问题, 双层模糊聚类, 改进遗传算法

Abstract: An improved genetic algorithm is proposed to solve the large-scale Multiple-Depot Vehicle Routing Problem（MDVRP）, which is based on the presented two-stage fuzzy clustering algorithm. In the first stage, k-means is used to divide the MDVRP into several sub-problems. In terms of improving the customer satisfaction and integrating logistics resource, fuzzy clustering algorithm is applied to cluster customers into groups based on multi-attribute customer orders. Furthermore, the improved GA is designed to solve the VRP by changing the selecting operator and the crossover operator. The stochastic simulation experiments show the proposed algorithm is efficient.

Key words: Multiple-Depot Vehicle Routing Problem（MDVRP）, two-stage fuzzy clustering, improved Genetic Algorithm（GA）