长沙集装箱多式联运优化研究
长沙集装箱多式联运优化研究(开题报告,外文翻译,论文27000字)
摘要
随着我国经济与对外贸易的蓬勃发展，绿色环保、节能高效的集装箱多式联运得到我国的重视和支持。国家相继出台一系列政策措施，用于推进我国集装箱多式联运的发展。长沙市作为湖南省政治、经济、文化、交通中心，同时是华中及长江中游地区主要的中心城市和经济中心之一，要把握“一带一路”机遇，发展集装箱多式联运，提高运输效率，促进经济发展。根据我国《海商法》中关于多式联运的概念和多式联运实情，本文主要针对长沙铁水联运进行分析，发现长沙集装箱多式联运发展过程中存在水运区位优势不足、联运基础设施存在短板、法律法规不适用、技术装备落后等问题。在此背景下，需要从集装箱多式联运量、运输路径与运输方式优化、对策等方面为长沙优化集装箱多式联运提供意见。
论文首先分析了长沙集装箱多式联运发展现状，揭示长沙港发展中存在的问题。为探究长沙港发展集装箱多式联运的空间，建立GM(1,1)-加权马尔科夫链模型对未来长沙港集装箱吞吐量进行预测。根据国际上铁水联运的比例，结合我国运输现状、国家政策，计算铁水联运集装箱的数量。结果表明，长沙港在未来几年集装箱吞吐量稳步提升，且增长速度逐年加快，至2025年，长沙港集装箱铁水联运将超过5万TEU。
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其次构建长沙集装箱多式联运组合优化模型，以运输费用最低、时间最短、碳排放量最少作为目标，运用遗传算法求解得出长沙至上海的集装箱运输路径与方式组合。最终得出6个Pareto最优解。结论表明，在集装箱运输中采用多式联运在一定程度上提高成本，但是减少了运输时间和碳排放，起到了节能高效的作用。此外在最优的运输路径与方式的选择上，决策者可以根据运输货物的数量、价值进行综合判断。最后论文从规划、基础设施、服务模式、中欧班列、智能环保等角度为长沙集装箱多式联运优化提供建议。
论文从长沙集装箱多式联运现状出发，分析长沙开展联运的问题，计算得出未来集装箱联运量，构建集装箱多式联运组合优化模型得出长沙至上海的最优运输方式及路径，得出长沙集装箱多式联运优化对策。研究结论可为长沙运输部门制定运输政策提供参考。
关键词：集装箱多式联运；GM(1,1)-加权马尔科夫链模型；组合优化模型；遗传算法；
Abstract
With the vigorous development of China's economy and foreign trade, the green, environmentally friendly, energy-efficient and efficient container multimodal transport has received the attention and support of China. The state has successively issued a series of policy measures to promote the development of China's container multimodal transport. As the political, economic, cultural and transportation center of Hunan Province, Changsha City is also one of the main central cities and economic centers in the middle reaches of Central China and the Yangtze River. It is necessary to grasp the opportunity of “One Belt, One Road” to develop container multimodal transport, improve transportation efficiency and promote economic development. According to the concept of multimodal transport and the multimodal transport in China's Maritime Law, this paper mainly analyzes the combined transport of railway and water in Changsha. However, in the development process of container multimodal transport in Changsha, there are problems such as insufficient water transport location advantages, short-term infrastructure of intermodal transport, inapplicable laws and regulations, and backward technical equipment. Under this background, it is necessary to provide reference for Changsha to optimize container multimodal transport from the aspects of container multimodal transport volume, transportation route and transportation mode optimization and countermeasures. [资料来源：http://www.doc163.com]
Firstly, the paperanalysis the status quo of the development of multi-modal container transport in Changsha,and summarizes the problems in the development of Changsha Port. In order to explore the space for the development of container multimodal transport in Changsha Port, a GM (1,1)-weighted Markov chain model was established to predict the future container throughput of Changsha Port. According to the proportion of international iron and steel combined transport, combined with China's transportation status and national policies, the number of iron and steel intermodal containers is calculated. The results show that the container throughput of Changsha Port will increase steadily in the next few years, and the growth rate will accelerate year by year. By 2025, the container iron-water combined transport of Changsha Port will exceed 50,000 TEU.
Secondly, the Changsha container multimodal transport portfolio optimization model is constructed. With the lowest transportation cost, the shortest time and the least carbon emission as the goal, the genetic algorithm is used to solve the container transportation path and mode combination from Changsha to Shanghai. Finally, six Pareto optimal solutions are obtained. The conclusion shows that the use of multimodal transport in container transportation increases the cost to a certain extent, but reduces the transportation time and carbon emissions, and plays an energy-saving and efficient role. In addition, in the choice of the optimal transportation route and mode, the decision makers can make a comprehensive judgment based on the quantity and value of the transported goods. Finally, the paper provides suggestions for the optimization of multi-modal transport of Changsha container from the perspectives of planning, infrastructure, service mode, CEIBS, and intelligent environmental protection. [来源：http://www.doc163.com]
Based on the current situation of container multimodal transport in Changsha, this paper analyzes the problems of intermodal transport in Changsha, calculates the future container transport volume, and constructs a container multimodal transport portfolio optimization model to obtain the optimal transportation mode and path from Changsha to Shanghai. Multimodal transport optimization strategy. The conclusions of the study can provide a reference for the transportation policy of Changsha Transportation Department.
Key Words：Container multimodal transport; GM (1,1)-weighted Markov chain model; Combined optimization model; genetic algorithm
目录
第1章绪论 1
1.1 研究背景及意义 1
1.2 国内外集装箱多式联运研究综述 2
1.3 研究方法及技术路线 4
1.3.1 研究方法 4
1.3.2 技术路线 4
第2章长沙集装箱多式联运现状及发展趋势 6
2.1 国内外集装箱多式联运现状 6
2.1.1 国外集装箱多式联运 6
2.1.2 国内集装箱多式联运 6
2.2 长沙集装箱多式联运发展现状分析 7 [资料来源：http://doc163.com]
2.2.1 长沙货物运输现状 7
2.2.2 长沙集装箱多式联运的现状及条件分析 8
2.3 长沙集装箱多式联运存在的问题 12
2.3.1 水运区位优势不足 12
2.3.2 联运基础设施短板 12
2.3.3 法律法规标准不适用 12
2.3.4 技术装备水平落后 13
2.4 长沙集装箱多式联运发展趋势 13
第3章长沙集装箱多式联运量预测 14
3.1 灰色GM(1，1)与Verhulst模型建立与求解方法 14
3.1.1 GM(1，1)模型 14
3.1.2 Verhulst模型 15
3.1.3 模型精度的检验 15
3.2 马尔科夫链建模过程 16
3.2.1 状态的划分 16
3.2.2 建立状态转移概率矩阵 16
3.2.3 修正预测值 17
3.3 基于GM（1，1）—加权马尔科夫链的长沙集装箱吞吐量预测 17
3.3.1 长沙集装箱吞吐量现状分析 17
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3.3.2 对比分析GM(1,1)与Verhulst模型 18
3.3.3 建立GM（1，1）—加权马尔科夫链模型 21
3.3.4 至2025年长沙集装箱吞吐量预测 24
3.4 长沙港进行多式联运的集装箱量 25
第4章基于遗传算法的长沙集装箱多式联运组合优化研究 26
4.1 集装箱多式联运组合优化模型 26
4.1.1 问题描述 26
4.1.2 假设条件 26
4.1.3 符号说明 27
4.1.4 模型建立 28
4.2 遗传算法简介与步骤 28
4.2.1 遗传算法简介 29
4.2.2 基于遗传算法的集装箱多式联运组合优化的编码步骤 29
4.2.3 Pareto适应度 30
4.3 长沙集装箱多式联运组合优化分析 31
4.3.1 长沙集装箱多式联运问题描述 31
4.3.2 相关参数与符号数值 33
4.3.3 代码计算与Pareto最优集 33 [资料来源：https://www.doc163.com]
第5章长沙集装箱多式联运优化建议 38
5.1 做好多式联运规划工作 38
5.2 加快集装箱多式联运基础设施建设 38
5.3 强化联运服务模式的创新 38
5.4 充分发挥长沙中欧班列的优势 38
5.5 推进建设智慧化、生态化港口 39
第6章结论与展望 40
6.1 研究结论 40
6.2 展望 41
参考文献 42
附录A：灰色预测模型 44
附录B：集装箱多式联运组合优化模型代码 48
致谢 62
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