取送一体化多配送中心车辆路径问题的研究

发布时间：2018-08-09 13:22

【摘要】：物流配送是现代化物流系统的一个重要环节,它是指根据客户的订单需求,在配送中心进行分货、配货,并将配好的货物及时运送到客户。在配送业务中,存在许多决策优化的问题,其中车辆路径的优化对物流企业加快配送速度、提高服务质量、降低配送成本以及增加经济效益有较大的影响。根据配送中心数目的多少,车辆路径问题有单配送中心车辆路径问题和多配送中心车辆路径问题之分；根据客户服务需求,车辆路径问题有纯送货车辆路径问题、纯取货车辆路径问题和取送一体化车辆路径问题之分。但在实际中,往往存在的是取送一体化多配送中心车辆路径问题(Multiple Depot Vehicle Routing Problem with Simultaneous Pick-up and Deliveries, MDVRPSPD)。因此对取送一体化多配送中心车辆路径问题进行研究具有重要的现实意义。本文针对MDVRPSPD主要进行了以下几个方面的研究：首先,本文在对传统车辆路径问题进行理论研究的基础上,根据现实的需求,提出了更贴近现实的取送一体化的多配送中心车辆路径问题,并且建立了相应的数学模型；其次,本文对车辆路径的求解方法进行了分析和比较,指出了传统方法求解多配送中心车辆路径问题存在的不足,提出了增加虚拟配送中心的方法把多配送中心车辆路径问题转化成单配送中心车辆路径问题,然后再对单配送中心车辆路径问题进行求解；最后,针对遗传算法在求解单配送中心车辆路径问题时存在早熟收敛,易陷入局部最优解,本文提出利用云模型中云滴所具有的随机性与稳定倾向性,由正态云模型的X条件云发生器实现对交叉概率和变异概率的调整,从而提高了遗传算法的性能。最后将改进后的遗传算法应用于车辆路径问题的求解中,并将其求解的结果与传统方法求解结果进行了比较,体现了改进算其可行性和有效性。
[Abstract]:Logistics distribution is an important link in modern logistics system. It refers to the distribution and distribution of goods in the distribution center according to the customer's order demand and the timely delivery of the matched goods to the customer. In the distribution business, there are many problems of decision optimization, among which the optimization of vehicle routing has a great impact on logistics enterprises to speed up distribution, improve the quality of service, reduce the cost of distribution and increase economic benefits. According to the number of distribution centers, the vehicle routing problem can be divided into single distribution center vehicle routing problem and multi-distribution center vehicle routing problem; according to customer service demand, the vehicle routing problem has a pure delivery vehicle routing problem. The path problem of pure cargo vehicle and the vehicle routing problem of integration of pick-up and delivery. However, in practice, the vehicle routing problem of multi-distribution center is often (Multiple Depot Vehicle Routing Problem with Simultaneous Pick-up and Deliveries, MDVRPSPD). Therefore, it is of great practical significance to study the vehicle routing problem of multi-distribution center. This paper mainly studies the following aspects of MDVRPSPD: firstly, based on the theoretical research of the traditional vehicle routing problem, according to the actual needs, This paper puts forward the vehicle routing problem of multi-distribution center, which is closer to the reality, and establishes the corresponding mathematical model. Secondly, this paper analyzes and compares the methods of solving the vehicle path. This paper points out the shortcomings of the traditional method to solve the vehicle routing problem of multi-distribution center, and puts forward the method of adding virtual distribution center to transform the vehicle routing problem of multi-distribution center into single distribution center vehicle routing problem. Then the vehicle routing problem of single distribution center is solved. Finally, the genetic algorithm has premature convergence in solving the vehicle routing problem of single distribution center, which is easy to fall into the local optimal solution. In this paper, the random and stable tendency of cloud droplets in cloud model is used to adjust the crossover probability and mutation probability by the X condition cloud generator of normal cloud model, so as to improve the performance of genetic algorithm. Finally, the improved genetic algorithm is applied to the vehicle routing problem, and the results of the improved genetic algorithm are compared with those of the traditional method, which shows the feasibility and effectiveness of the improved algorithm.
【学位授予单位】：大连海事大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：F259.1

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