Abstract: Firstly, the paper establishes a mathematical model for Single-depot and Heterogeneous-vehicle vehicle routing problem(SHVRP)according to the actual situation of Zhengzhou coal electricity material supply and marketing limited company. Then based on the model, it uses improved genetic algorithm(IGA) to optimize the vehicle routing problem(VRP)of Zhengzhou coal electricity material supply and marketing limited company. Finally by comparing the performance of IGA with classical heuristics algorithm(CHA)and sweeping algorithm(SA)in solving distribution cost, the number of used vehicle and computing time , the results show that IGA obtains the best objective function value, SA takes the second place, and CHA is the poorest. However, from the number of vehicles used, the optimum solution of CHA uses the least vehicles, followed by SA and IGA, but CHA is most efficient in solving time, and the time needed for calculation is only two-fifths of that of SA, two-twonty-fifths of that of IGA.

Key words: logistics system management, vehicle routing problem, heterogeneous fleet, genetic algorithm, zhengzhou coal electricity material supply and marketing limited company

摘要： 首先根据郑州煤电物资供销有限公司的实际情况建立单车场多车型车辆路径问题的模型,在此模型的基础上,用本文提出的改进遗传算法(IGA)对其求解,最后通过和传统的启发式算法(CHA)、扫描法(SA)的求解从配送费用、配送车辆数和运算时间上进行了综合比较,得出IGA算法求得的总运输费用最低,SA算法次之,CHA算法最高;但从所需参与配送的车辆数目来看,CHA求得的最好解所需的车辆数最少,其次是SA,IGA最多;在平均计算时间上,CHA的优势最明显,仅为SA的,IGA的。

关键词: 物流系统管理, 车辆路径问题, 多车型, 遗传算法, 郑州煤电物资供销有限公司