摘要
对郑州煤电物资供销公司危险品运送的车辆路径问题进行了分析,建立了相应的数学模型,运用人工鱼群算法求解出运费最小的方案。该算法首先初始化一个鱼群,并在初始化的过程中给出了一种修复算子,使鱼群中每条鱼当前的状态代表一种可行的配送方案,然后执行本文设计的随机行为、觅食行为、聚群行为和追尾行为进行全局寻优。最后,把该算法与扫描算法、遗传算法求解进行比较,证明了人工鱼群算法求解车辆路径问题的有效性;同时,该算法也拓展了求解VRP问题的算法空间。
The paper is concerned with the vehicle routing problem for dangerous goods distribution in Zhengzhou Coal Material Supply and Sales Company. We establish the mathematical model for the problem and solve the problem by an artificial fish-swarm algorithm. Firstly, a school of artificial fish is initialized with a repair operator to guarantee that each fish denotes a feasible transportation plan. The process for global optimization is subsequently developed by using random behavior, prey behavior, swarm behavior, and following behavior. Compared with the results produced by sweep algorithm or genetic algorithm, the results of artificial fish-swarm algorithm show that the algorithm has relatively good performance for solving the vehicle routing problem. The research provides a new approach to the vehicle routing problem.
出处
《系统管理学报》
CSSCI
2012年第3期341-351,共11页
Journal of Systems & Management
基金
国家自然科学基金青年科学基金资助项目(71103163
71103164)
中国博士后基金资助项目(20090461293)
中国博士后科学基金特别资助项目(201003670)
教育部人文社会科学研究青年基金资助项目(10YJC790071)
中央高校基本科研业务费专项资金资助项目(CUG090113
CUG110411
G2012002A)
关键词
车辆路径问题
人工鱼群算法
扫描算法
遗传算法
vehicle routing problem
artificial fish-swarm algorithm
sweep algorithm
genetic algorithm
