近年来,物流作为“第三方利润的源泉”受到国内各行业的极大重视并得到了较大的发展。在高度发展的商业社会中,传统的VSP算法已无法满足顾客需求对物流配送提出的要求,于是时间窗的概念应运而生。带有时间窗的车辆优化调度问题是比VSP复杂程度更高的NP难题。
本文在研究物流配送车辆优化调度问题的基础上,对有时间窗的车辆优化调度问题进行了分析。并对所采用的遗传算法的基本理论做了论述。
对于有时间窗的非满载VSP问题,将货运量约束和软时间窗约束转化为目标约束,建立了非满载VSP模型,设计了基于自然数编码,使用最大保留交叉、改进的反转变异等技术的遗传算法。经实验分析,取得了较好的结果。由于此问题为小组成员共同研究,本文重点论述了本人完成的关于适应度函数和变异操作的部分。
关键词:物流配送 车辆优化调度 遗传算法 时间窗
Recent years, logistics, taken as "third profit resource”, has been developing rapidly. In the developed commercial society, traditional VSP algorithm have been unable to meet the requirement that Quick Response to customer demand had brought forth, then the conception of Time Window has come into being. The vehicle-scheduling problem with time window is also a NP-hard problem being more complicated than VSP.
This text has been researched to the vehicle-scheduling problem with time window on the basis of researched to logistic vehicle scheduling problem. And it has explained the basic theory of genetic algorithm.
On the VSP with time window, while the restraints of capacity and time windows are changed into object restraints, a mathematic model is established. We use technique such as maximum preserved crossover and design genetic algorithm on nature number, which can deal with soft time windows through experimental analysis, have made better result. Because this problem was studied together for group members, this text has expounded the part about fitness function and mutation operator that I finished.
Key words: logistic distribution vehicle scheduling problem genetic algorithm time windows