计算机工程与应用Issue(5)：261-264,270,5.DOI:10.3778/j.issn.1002-8331.1204-0559
基于双层模糊聚类的多车场车辆路径遗传算法
Two-stage fuzzy clustering genetic algorithm for multiple-depot vehicle routing problem
摘要
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. Further-more, 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.关键词
多车场车辆路径问题/双层模糊聚类/改进遗传算法Key words
Multiple-Depot Vehicle Routing Problem(MDVRP)/two-stage fuzzy clustering/improved Genetic Algorithm(GA)分类
信息技术与安全科学引用本文复制引用
李波,邱红艳..基于双层模糊聚类的多车场车辆路径遗传算法[J].计算机工程与应用,2014,(5):261-264,270,5.基金项目
教育部新世纪优秀人才支持计划资助项目（No.NCET-06-0236）；高等学校博士学科点专项科研基金资助项目（No.20100032110034）。 （）
