【作者】 东方；

【导师】 杨华龙；

【作者基本信息】 大连海事大学 ， 物流工程与管理， 2010， 博士

【摘要】 集装箱多式联运运输服务是以集装箱为媒介,把水路、公路、铁路以及航空等多种运输方式有机地组织衔接为一体,采用两种或两种以上不同运输方式,为托运人提供“全程式”和“一票式”运输的物流服务。集装箱多式联运运输服务采购是托运人为实现其生产、销售目的或延伸其综合运输网络能力,从运输市场获取其需要的多式联运服务,以对其(集装箱)货物进行运输。集装箱多式联运运输服务采购的组合优化,是指从集装箱托运人的角度,按照利益最大化的原则,选择最佳的多式联运服务承运人组合,其最终目的就是以最佳的运价、效率和服务质量获得其需要的运输服务。在集装箱多式联运运输服务采购中,集装箱货主为了实现货物的连贯运输,一般通过多式联运经营人来具体选择和落实各分段运输服务。因此,本文研究的集装箱多式联运运输服务采购行为涉及了三类参与者,即：集装箱货主、多式联运经营人和区段运输承运人。上述三类参与者在具体的集装箱多式联运运输服务采购行为中要么是运输服务的采购方(托运方),要么则是运输服务的供给方(承运方)。在多式联运包干运输服务采购中,托运方是集装箱货主,承运方是提供全程运输服务的多式联运经营人。而在多式联运分包运输采购中,多式联运经营人则成为采购行为中的采购方,承运方是区段运输承运人。本文研究从托运方角度来探讨集装箱多式联运运输服务采购问题,对以往托运人的定向化运输服务采购模式在组合优化方面做出改进和探索,使用组合优化方法对多式联运中运输服务的最佳组合状态进行分析,研究集装箱多式联运包干运输服务采购(从集装箱货主角度)和集装箱多式联运分段运输服务采购(从多式联运经营人角度)中的运输服务组合优化问题。针对当前研究的问题,本文从三个方面展开了具体研究：(1)针对集装箱多式联运包干运输服务的采购行为,建立以包干运费、服务质量、承运人信誉、运网能力为属性的多属性组合拍卖的组合优化模型,探讨集装箱货主选择多式联运经营人服务的组合优化方法。首先,文中对集装箱多式联运运输服务采购中的评价属性建立了评价指标体系,权衡了几个主要属性目标对集装箱货主选择运输服务的影响情况,确定了各属性的权重系数；其次,对多式联运运输服务采购的组合拍卖过程和竞胜标结果进行模拟和分析,建立了一套多目标混合整数规划的组合优化模型；最后,引入属性状态向量间“欧式距离”的概念,将上述多目标混合整数规划问题转化为单目标规划问题,探讨集装箱多式联运包干运输服务采购的组合优化问题。(2)针对集装箱多式联运分段运输服务的采购行为,建立以运费最小化和运输环节一体化无缝衔接为目标的服务组合优化模型,研究多式联运经营人以托运人身份选择区段运输服务的组合优化方法。首先,通过对多式联运实际运输区段服务涉及的各个要素进行分析,确定区段运输服务采购中的变量参数；其次,分析各变量参数的数据结构,引入“数值”结构的时间变量和“非数值”结构的地点变量,建立基于前后段运输方式相衔接的混合整数规划非线性模型,探讨集装箱多式联运分段运输服务采购的组合优化问题。(3)为实现上述集装箱多式联运包干运输服务和分段运输服务托运中的组合优化目的,对上述问题中的混合整数规划非线性模型进行算法设计,建立集装箱货主和多式联运经营人服务采购的组合优化算法模型,使用集合推理、逻辑推理、启发式搜索的方法对组合优化模型进行联合推理,实际解决多式联运包干运输和分段运输服务的组合优化问题。更多还原

【Abstract】 Multi-modal transportation service connects the transportation modal of sea, road, rail, air and others as one system, by the medium of containers, which provides "whole course, one document" transport logistics services to the shippers. Multi-modal transportation service purchase is definited as the process of obtaining the service requirements from the multi-modal transportation market services to containers transport, for the purpose of implementing production or extending the transportation network,. Multi-modal transportation service purchase optimization is definited from the perspective of the shippers and the principal of the shippers’maximum benefit, to choose the best carrier combination. The ultimate target of transportation service purchase is to pursue the opimum freight, efficiency and quality of transportation services.During the process of multi-modal transportation service purchase, in order to achieve the coherent transportation of the container cargos, the shppers usually select the sectional transport services through the multimodal transport operators. In this paper, there are three kinds of participants during the course of container transport service purchase:the real shppers, the multi-modal transport operator(MTO) and the section al transport carrier. The participants must be the purchase party(the shipper) or the supply party(the carrier). In the multi-modal transportation sum services purchase process, the shipper party is the real shipper of containers, and the carrier party is the multi-modal transport operator who provides sum transportation service. In the multi-modal transport segmental service purchase process, the shpper party is the multi-modal transport operator, and the carrier party is the sectional transport carrier.In this paper, the research fo multi-modal transport services purchase is discussed from the perspective of the shipper party, which explores the use of combinatorial optimization methods for oriented multi-modal transport services and its improvement. The optimum combinational state is analyzed, which involves both service purchase of sum transport(from the perspective of the container owner) and segmental transport (from the perspective of the multimodal transport operator).Regarding to the research, the following three aspects are studied in this paper:(1) For the sum transport service purchase study, a series of multi-attribute combinatorial optimization models are established, regarding to the freight, service quality, carriers’ reputation, and their transport network capacity. Firstly, the evaluation index for multi-mode transportation operator is established, and the weight coefficients of the main attribute are given through balance idea. Secondly, the combination process of multi-modal transportation services purchase with combinatorial auction and bidding competition is analyzed and simulated. Also, the multi-objective mixed integer programming model for combinatorial optimization is established. Finally, the concept of Euclidean distance formula of state vector is introduced in the study and the multi-objective mixed integer programming problem can be turned into a single objective programming problem to discuss combinatorial optimization problems in multi-modal container transportation services purchase.(2) For the section transport service purchase study, the combinatorial optimization model is established, aiming at the minimum sum freight and the jointless connection for the transportation links. This paper studied the combinatorial optimization method for the multimodal transport operators to select the sectional transport services as shippers.First of all, analyze all the elements in the actual sectional transport service, and determine the variable parameters in the service purchase. Secondly, analyze the data structures of variable parameters, and introduce the value structure of the time variable and non-numerical structure of the site variables. Then the nonlinear mixed integer programming model is established based on convergence of transport modes before and after.(3) To achieve the above optimization purposes of purchase of both sum transport services and sectional transport services of multi-modal transoportation, the algorithm are designed for the above problems of nonlinear mixed integer programming models, involving both the multimodal transport operators and the real container shippers. Through the cooperate reasoning of set reasoning, logical reasoning, ane heuristic search, the optimization model for sum transporat service and segtional transport service of the multi-modal transportation services purchase optimization problems could be solved and realized at last.更多还原