【作者】 朱琳；

【导师】 李波；

【作者基本信息】 天津大学 ， 管理科学与工程， 2010， 硕士

【摘要】 随着企业全球化及外包化的发展,大规模物流配送成为目前很多企业面临的主要问题。其中涉及的生产地分布广,产品品项众多,而客户需求波动很大,致使物流配送零担现象增加等。为了能降低物流配送的成本,同时又快速响应客户的需求,减少配送中的零担现象,车辆配载规划与调度成为研究的热点。本文基于这种研究背景,提出了一种带有优先级别的两层次车辆配载规划与调度方法。引入了一种改进的人工免疫算法(Artificial Immune Algorithm, AIA),通过发展此算法思想及系统聚类思想,提出了一个两层次的车辆配载聚类方法。聚类算法分成两层次:首先,上层次根据客户地理位置的分布进行需求客户群的聚类,这一层次的聚类仅考虑客户的定位,而不考虑物流配送的需求;然后,把客户需求订单按照调度周期进行排序,形成待调度的车辆配载队列。针对此队列进行下层次的车辆配载货物的调度聚类方案。此时,算法基于客户订单大小、客户需求品项的多样性及其配送中产品单位的不可再分性等特性,定义了一系列启发式规则,考虑租用车辆数最少且允许客户分割情形下,建立了数学模型。最后,结合启发式策略和多种分优先级别的聚类策略,给出考虑客户不同产品品项配送完整性和路径选择最短来生成车辆配载聚类的方案。一方面,上层次的AIA客户聚类算法为下层次车辆配载聚类缩小了规划与调度的范围;另一方面,下层次带启发式规则和优先级别的聚类模型是针对某调度周期内一个具体的客户群车辆配载方案的实现。对于实际中大规模的物流配送问题,本文上下两层聚类算法的设计大大减少了算法的复杂性,可得到问题的最优解。最后,对模型进行仿真实验,详细阐述了算法运行步骤,及算法思想体现,说明了提出方法的有效性。更多还原

【Abstract】 With the development of globalization and outsourcing, logistics distribution in a large scale has become an important problem facing many enterprises, which processes the characteristics of dispersed distribution, abundant product categories, frequent undulation of customer demand, increasing in the situation of less-than-carload(LCL) freight transport. In order to cut down the cost of logistics,respond to market demand quickly and reduce the LCL situation, loading optimization and dispatching has attracted more and more attention.In this paper, a novel method called two level clustering using in resolving the problem of loading optimization has been proposed based on the mentioned background. By introducing an improved algorithm of Artificial ImmuneAlgorithm(AIA) with developing the ideas of this algorithm and systematic clustering the two level clustering method has been presented. The algorithm has the structure of, two layers. Firstly, implementing the upper level of the algorithm can achieve theeffect of grouping the customers into several clusters according to their positions. This stage has just taken the customer location into account without considering theneeds of theirs. Secondly, sort the orders according to the dispatching cycle, form a fleet remained to be assigned. Then, the dispatching plan calculated from the second level of the algorithm can be obtained. Therefore, based on the size of order, the diversity of product and the smallest split unit of product, several heuristic rules has been defined with consideration of using the minimal number of vehicles and allowing to split circumstances. The specific model has been designed as well. Finallyby combining the heuristic strategy and multi-level priorities strategy, the solution,, which takes the accuracy of delivery goods and the shortest route option into account, has been obtained. On the one hand, the algorithm of the upper level has been used to the calculation amount of the lower level. On the other hand, the model of lower levelwith heuristic rules and priority levels has been used to resolve the problem of each cluster. Thus, the presented algorithm can dramatically reduce the complexity and obtain the optimal solution of the problem. At last, simulation experiment has been carried out. The procedure and ideas have been illustrated to evaluate theeffectiveness of the algorithm.更多还原