Abstract: The logistics distribution vehicle scheduling problem is to arrange distribution efficiently with limited resources. The optimization goal is to obtain a program which has lower cost with the constraints of the requirements of the users and the conditions of the vehicles. Affected by many factors, such as the location and requirement of customers, and the transport capacity of delivery vehicles, the vehicle scheduling problem is very complicated. A mathematical model of the double-way vehicle scheduling problem is established, considering the mile limit and user limit, and referring to the classic vehicle routing problem model. Based on the particle swarm optimization, a distribution vehicle scheduling algorithm is given. And by using hill-climbing methods, the local searching ability of the particle swarm optimization algorithm is improved.

Key words: logistics distribution, vehicle scheduling, particle swarm optimization, hill-climbing method

摘要： 物流配送车辆调度问题是指安排有限的车辆有效地完成配送任务。优化目标是在满足客户需求和车辆能力约束的条件下，找出配送成本较低的配送车辆调度方案。由于配送过程受客户位置、配送车辆限制等多种因素影响，导致车辆的调度问题十分复杂。参照经典车辆路径问题模型，考虑了车辆配送里程和用户数等限制，建立了双向车辆调度问题的数学模型。在标准粒子群算法的基础上，引入爬山操作，增加了粒子群的多样性，提高了算法的局部搜索能力，并设计了基于改进粒子群算法的物流配送车辆调度算法，有效地解决了物流配送车辆的优化调度问题。

关键词: 物流配送, 车辆调度, 粒子群优化算法, 爬山算法