摘要
针对不确定车辆数的车辆调度问题,建立了使用配送车辆数最少和总行驶距离最短的双目标数学规划模型.在分层序列法思想的框架内,提出一种分两阶段求解的混合算法.基于改进的粒子群算法进行车辆的分配,获得完成任务集所使用的最少车辆数,把粒子群的优化方案转化为禁忌算法的初始解进行路径的优化,以使车队完成给定的配送任务集所花费的成本最少.通过实例求解结果对算法进行了总结分析.
A two-objective module is established to minimize needed vehicles and travel distance for variable fleet vehicle routing problem.A hybrid algorithm composed of improved particle optimization and tabu search is proposed and divided into two-phase to slove based on goal programming method.At first,cargos are distributed by PSO（particle swarm optimization）,and then,translated the optimization schedule in the first phase into the initialization of tabu search algorithm to optimize path,aiming to minimize the general cost. Finally, the hybrid algorithm was analyzed according to the result of real example.
出处
《武汉理工大学学报（交通科学与工程版）》
2009年第4期647-650,共4页
Journal of Wuhan University of Technology（Transportation Science & Engineering）
基金
交通部科技项目资助(批准号:200439800060)
关键词
禁忌搜索算法
混合算法
二阶段
改进粒子群优化
tabu search algorithm
hybrid algorithm
two-phase
improved particle swarm optimization
