物流配送系统中车辆调度问题智能优化方法研究

摘要在如今高速发展的社会，尤其是随着网络及电子商务的发展，物流配送系统越发显得重要，在物流配送过程中配送的成本在所有成本中占据最高的位置。而配送主要是指物流配送中心安排车辆完成配送，这类问题也称为车辆调度问题（VSP）。因此，合理安排车辆对于物流中心的效益有很大关系。近年来，物流系统中的车辆调度问题（VSP）成为了当今学者们争相研究的一个课题。本文首先分析车辆调度的问题，根据问题的繁琐程度进行区分；然后，通过约束的条件以及优化的目标来确定VSP的数学模型。车辆调度问题属于NP问题，所以很难获得精确解。而近年来随着智能优化算法的快速发展，为解决该类问题提供了有竞争力的解决方案。本文选取其中典型算法遗传算法作为求解工具，根据遗传算法的特点，合理设计算法流程，实现了通过遗传算法来解决车辆调度问题中非满载的情况。仿真结果表明所提出的算法具有一定的优越性，这也为后续相关研究打下了坚实的基础。73698

该论文有图13幅，表6个，参考文献23篇。

毕业论文关键词：物流配送车辆调度遗传算法非满载

The Research on Intelligent Optimization Method of Vehicle Routing Problem in Logistics Distribution System

Abstract In this rapid development of society, especially with the development of Internet and electronic commerce, logistics distribution system appears more and more important。 In all kinds of item cost, distribution cost in the process of logistics distribution occupies the highest position。 Distribution mainly refers to that the logistics distribution center arranges vehicles to complete the delivery。 This kind of problem is also known as the vehicle scheduling problem (VSP)。 Therefore, it can benefit the logistics center a lot in the reasonable arrangement of the vehicle。 In recent years, the logistics system of vehicle scheduling problem (VSP) became a subject that today's scholars try to research before others。 This paper analyses the vehicle scheduling problem first。 It is distinguished according to the complicated degree of the problems。 Then, the mathematical model of VSP can be determined by constraining conditions and the optimization target。 Vehicle scheduling problem belongs to NP problem。 So it is difficult to obtain the exact solution。 In recent years, with the rapid development of intelligent optimization algorithm, it provides a competitive solution to solve this kind of the problem。 This article selects the typical algorithm of genetic algorithm as a tool, based on the characteristics of genetic algorithm and a reasonable process design algorithm, to solve non-full load condition in the vehicle scheduling problem by genetic algorithm。 The simulation results show that the algorithm has the certain superiority。 It also laid a solid foundation for follow-up research。

Key Words: logistics distribution vehicle scheduling genetic algorithm non-full load

摘要 I

Abstract II

目录 III

图清单 V

表清单 V

变量注释表 VI

1 绪论 1

1。1物流配送系统简述 1

1。2车辆调度的研究成果及发展 2

1。3车辆调度研究方法 3

1。4论文的结构安排 6

2 车辆调度分类及数学描述物流配送系统中车辆调度问题智能优化方法研究:http://www.youerw.com/zidonghua/lunwen_84114.html