考虑班期限制的货物多式联运路径优化研究

发布时间：2018-04-05 23:31

本文选题：综合运输　切入点：多式联运　出处：《重庆交通大学》2017年硕士论文

【摘要】：随着我国交通网络结构越来越完善,以及综合枢纽的建成,多式联运发展迅猛,也越来越受物流企业欢迎。但目前多式联运也存在不少问题,如节点中转效率低、时效性不高、信息不畅通等。为了进一步推动多式联运蓬勃发展,突破这些制约瓶颈势在必行。在货物多式联运实际运输过程当中,运输路径和运输方式的选择是获得最优运输路径的关键影响因素,其中运输费用、运输时间、运输风险是决定多式联运整体运输服务水平是否达到货物委托企业要求的决定因素。本文通过将班期限制约束和货损系数考虑到多式联运的路径优化研究中去,扩展优化为考虑班期限制的货物多式联运路径优化模型,并根据问题实际情况设计遗传算法对模型进行求解。本文的主要研究内容如下:(1)大量查阅整理近几年与多式联运相关的文献资料,对多式联运基础性工作以及国内外研究现状进行分析,指出当前研究存在的不足,提出论文的研究方向和研究内容;(2)总结分析货物多式联运路径优化影响因素,并提出以运输费用、运输时间、运输风险为目标函数的货物多式联运路径优化原始模型,详细阐明班期限制在模型中的刻画思路,进而将原始模型扩展优化为考虑班期限制的货物多式联运路径优化模型;(3)模型中对运输费用、运输时间、运输风险三个目标函数进行量纲为1处理,并乘以相应的权重系数,与一般的单目标模型相比,在做最优路径决策时能更好的满足客户在运输费用、运输时间、运输风险三者之间侧重需求;(4)在多式联运网络进行剖析分析基础上,设计了基于遗传算法的多式联运路径优化模型求解步骤。详细阐述了层次分析法确定运输因素权重过程,并运用该方法确定了一般货物,易碎、易潮货物,生鲜、冷冻货物多式联运目标函数中运输费用、运输时间、运输方法的权重系数;(5)以企业委托第三方物流将一批重达200吨的一般货物从重庆运往上海为例,运用遗传算法对未考虑班期限制和考虑班期限制两种模型(即原始模型和扩展优化模型)进行求解,并对结果进行对比分析。通过研究结果分析可以发现,城市节点火车、货轮等运输方式固定的发班时间对最优路径选择有较大影响,将班期限制约束考虑到多式联运路径优化模型中去,物流企业可以得到更加合理的运输方案。本文创新点主要有以下几点:(1)本文在建立多式联运路径优化原始模型时,将货损系数和危险抵消因子融合到其中,区别以往以单纯事故概率定量风险程度;(2)本文从多式联运实际运输情况出发,将班期限制约束和货损系数考虑到多式联运路径优化原始模型中,使模型更加贴合实际情况;(3)本文在求解模型时,先将多式联运网络进行剖析,再进行编码,可以降低编码难度,缩短程序运行时间。
[Abstract]:With the improvement of traffic network structure and the construction of integrated hub, multimodal transport is developing rapidly and is more and more popular with logistics enterprises.However, there are still many problems in multimodal transport, such as low efficiency of node transfer, low timeliness, and unimpeded information.In order to further promote the vigorous development of multimodal transport, it is imperative to break through these constraints.In the actual transport process of multimodal transport of goods, the choice of transportation route and mode of transport is the key factor to obtain the optimal transportation path, including transportation cost, transportation time,Transportation risk is the decisive factor to decide whether the service level of multimodal transport can meet the requirements of consignments.In this paper, the restriction of shift time and the loss coefficient are taken into account in the study of route optimization of multimodal transport, and the model of route optimization of cargo multimodal transport is extended to take into account the limitation of shift period.A genetic algorithm is designed to solve the model according to the actual situation of the problem.The main research contents of this paper are as follows: (1) A large number of documents related to multimodal transport in recent years have been reviewed, the basic work of multimodal transport and the current research situation at home and abroad have been analyzed, and the shortcomings of the current research have been pointed out.This paper puts forward the research direction and research content of the paper, summarizes and analyzes the factors affecting the route optimization of multimodal transport of goods, and puts forward the original model of route optimization of multimodal transport of goods based on the objective function of transportation cost, transportation time and transportation risk.The description of shift limitation in the model is explained in detail, and then the original model is extended to the freight multimodal transport route optimization model considering shift limitation.The three objective functions of transportation risk are processed in dimension 1 and multiplied by the corresponding weight coefficient. Compared with the general single objective model, the transport risk can better meet the customer's transportation cost and time when making the optimal path decision.On the basis of analyzing and analyzing the multimodal transport network, the steps of solving the path optimization model of multimodal transport based on genetic algorithm are designed.The process of determining the weight of transportation factors by analytic hierarchy process (AHP) is described in detail, and the transportation cost and time in the objective function of multimodal transport of general goods, fragile, damp goods, fresh and frozen goods are determined by using this method.The weight coefficient of the transportation method is 5) taking the third party logistics commissioned by the enterprise to transport a batch of general goods weighing up to 200 tons from Chongqing to Shanghai as an example.The genetic algorithm is used to solve the two models (the original model and the extended optimization model) without or without the limit of shift duration, and the results are compared and analyzed.Through the analysis of the research results, it can be found that the fixed departure time of urban node trains and freight vessels has great influence on the optimal route selection, and the restriction of shift duration is taken into account in the route optimization model of multimodal transport.Logistics enterprises can get more reasonable transportation plan.The main innovations of this paper are as follows: 1) in the course of establishing the original model of multimodal transport route optimization, this paper combines the damage coefficient and the risk offsetting factor into the original model.Based on the actual transportation conditions of multimodal transport, this paper considers the shift restriction and damage coefficient into the original model of route optimization for multimodal transport.In this paper, the multimodal transport network is analyzed first and then coded, which can reduce the difficulty of coding and shorten the running time of the program.
【学位授予单位】：重庆交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U116.2

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