摘要
针对微粒群优化算法容易陷入局部极值的缺陷,提出多相粒子群优化算法(Multi-pha-ses Particle Swarm Optimization,MPSO)。建立了带软时间窗车辆调度问题数学模型,并将该方法运用于带软时间窗车辆调度路径优化。根据多相粒子群并行搜索的思想,给出MPSO算法在带软时间窗物流配送车辆调度路径优化的实现流程。仿真结果表明:多相粒子群算法可以快速、有效地求得车辆路径问题的优化解,是一种求解带软时间窗车辆路径问题的较好方案。
In order to improve the performance of particle swarm optimization algorithm （PSO）, a new multi-phases particle swarm optimization algorithm （MPSO） is proposed in this paper, which is further applied to the optimization problem of a vehicle scheduling with soft time windows. By means of the idea of parallel search, the detailed procedure of the MPSO algorithm is given for solving vehicle scheduling problem with soft time windows. The simulation results show that the proposed MPSO is feasible for the problem of vehicle scheduling with soft time window.
出处
《华东理工大学学报（自然科学版）》
CAS
CSCD
北大核心
2009年第5期774-778,共5页
Journal of East China University of Science and Technology
基金
国家自然科学基金(60774078)
上海海洋大学博士启动基金项目(A-3605-08-0225)
关键词
多相粒子群算法优化
车辆调度问题
软时间窗
路径优化
multi-phases particle swarm optimization
vehicle scheduling problem
soft time windows
route optimization
