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论文编号：	5347
作者编号：	2120112360
上传时间：	2013/6/6 17:29:26
中文题目：	供给能力有限的可拆分车辆路径问题研究
英文题目：	Research on Spilt Vehicle Routing Problem with Limited Supply
指导老师：	张建勇
中文关键字：	需求可拆分；车辆路径问题；遗传算法；插入法
英文关键字：	Split Demand ; Vehicle Routing Problem ; Genetic Algorithms ; Insertion Method
中文摘要：	运输是整个物流活动体系中非常重要的一个环节，贯穿着生产和销售的整个过程。通常，运输成本在企业的运营成本中占有较大的比重，尤其是在加工制造，能源等行业。同时，运输的高效性也对企业的仓储、生产和管理等环节有着很大影响。另外，作为联系企业和最终用户的纽带和桥梁，运输的效率直接影响着企业对客户需求的响应速度，影响客户对企业服务的满意程度。因此，运输环节的优化程度对于企业运营成本的降低，运行效率的提高以及竞争力的提高有着至关重要的影响。 车辆调度是运输环节优化的关键所在，其要解决的问题是如何在满足各种限制条件下，如车辆载重量，时间和客户需求量等，合理安排车辆的行驶路线和对客户进行服务的顺序，以达到降低运输成本的目的。合理的车辆调度方案能够有效地降低物资运输成本，提高运输效率。可拆分车辆路径问题作为车辆路径问题的一个重要分支，具有更切合车辆配送的实际情况，更能满足企业经营管理的实际需求的特点，因此在理论研究方面也得到越来越多的关注。 本文研究了在配送中心供给能力有限且客户点需求允许拆分配送情况下的车辆路径问题。全文首先对所研究问题的研究背景和研究意义进行了简单的介绍，通过回顾并总结现有研究的成果及不足，提出了本文的研究问题。然后在不同的考虑因素下构建了相应的整数规划模型，并根据模型的特点对遗传算法中的种群生产方法和遗传算子进行了设计，最后运用所设计的自适应遗传算法对随机生成的算例进行了求解分析，验证了模型的合理性以及算法的有效性。 本文的创新点主要在于综合考虑了车辆调度过程中车辆的行驶路线以及配送中心的资源配置问题，对传统的可拆分车辆路径问题模型进行了改进，并设计了适用于求解该问题的遗传算法。文章最后指出了本研究仍存在的不足以及该领域未来的研究方向。
英文摘要：	Transportation is a very important link of logistics activities, throughout the entire process of production and sales. Typically, the transportation costs account for a large proportion of the cost of enterprise operation, especially in the manufacturing, energy and other industries. The same time, the efficiency of transportation has a great impact on warehousing, production and management and other aspects of enterprise operation. In addition, as a link between the enterprises and end users, Transport efficiency directly affects the enterprise response speed to customer's requirement and the customer satisfaction of enterprise service. Therefore, transportation optimization helps enterprise to reduce costs, improve operational efficiency and market competitiveness. Vehicle scheduling is the key point of the optimization of transportation, it wants to deal the problem how to arrange the reasonable vehicle route to service the customers with meeting a variety of restrictions, such as vehicle load capacity, time and customer demand, the purpose of this problem is to reduce the transportation costs. The reasonable vehicle scheduling scheme can effectively reduce the cost of transportation of materials and improve the transport efficiency. Split vehicle routing problem as an important branch of the vehicle routing problem, it is more in line with the actual situation of vehicle delivery and better meet the actual needs of the enterprise management features, has attracted more and more attention in theoretical research. This paper studies the split demand vehicle routing problem with limited supply. Firstly, this paper briefly introduces the research background and the significance, proposes the research problem by review and sum up the achievements and shortcomings of the existing research. Secondly, this paper builds different integer programming model with considering different factors, and then designs the corresponding genetic algorithm. Finally, this paper uses the adaptive genetic algorithm to solve a case which is generated randomly to verify the rationality of the model and the effectiveness of the algorithm. The main innovation of this paper is to consider the issue of vehicle scheduling and resource allocation comprehensively, improve the traditional vehicle routing problem model and design the genetic algorithm used to solve the problem. At last, this paper points out that the shortcomings and prospects for future researches in this research directions.
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