基于顾客满意的物流协同配送路径优化研究
发布时间：2018-10-29 15:39
【摘要】：配送中心在进行物流配送时往往忽略了各配送中心之间相互协作、共同承担配送任务和风险的问题，造成资源浪费，利用率低等。协同配送最大限度地提高人员、物资、金钱、时间等物流资源的利用效率，提高物流配送的响应速度和物流服务水平，，取得最大社会效益，还可以减少物流设施重复建设，实现物流设施合理布局，并取得缓解交通拥挤、保护环境等社会效益。因此研究协同配送路径问题对于提高配送效率、减少配送成本具有重要意义。 本文首先论述了研究背景和研究意义，分析了国内外研究现状，阐述了协同配送和顾客满意的相关理论；其次，通过对经典路径优化数学模型的分析，以及顾客满意的数学实现过程分析，建立了基于顾客满意的物流协同配送路径优化模型，模型建立时考虑了协同配送的特殊配送方式和配送的实效性，同时考虑了顾客满意对于配送选择的影响；再次，概述了遗传算法和蚁群算法的基本原理和算法的优缺点，并给出了遗传蚁群算法的设计思想和基本步骤；最后，阐述了路径优化的算法设计，并进行了算例研究，验证了模型的有效性和可行性。
[Abstract]:Distribution centers often ignore the cooperation between distribution centers and share the distribution tasks and risks, resulting in waste of resources, low utilization rate and so on. Collaborative distribution maximizes the utilization efficiency of logistics resources such as personnel, materials, money, time, and so on, improves the response speed of logistics distribution and the level of logistics service, obtains the greatest social benefits, and can also reduce the duplication of construction of logistics facilities. Realize reasonable distribution of logistics facilities, and achieve social benefits such as alleviating traffic congestion and protecting environment. Therefore, it is of great significance to study cooperative distribution path for improving distribution efficiency and reducing distribution cost. Firstly, this paper discusses the research background and significance, analyzes the current research situation at home and abroad, and expounds the related theories of collaborative distribution and customer satisfaction. Secondly, through the analysis of the classical path optimization mathematical model and the mathematical realization process of customer satisfaction, the logistics collaborative distribution path optimization model based on customer satisfaction is established. When the model is established, the special distribution mode and the effectiveness of collaborative distribution are considered, and the influence of customer satisfaction on distribution selection is considered. Thirdly, the basic principles and advantages and disadvantages of genetic algorithm and ant colony algorithm are summarized, and the design idea and basic steps of genetic ant colony algorithm are given. Finally, the algorithm design of path optimization is described, and an example is given to verify the validity and feasibility of the model.
【学位授予单位】：河北工程大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F252;TP18
本文编号：2298105
[Abstract]:Distribution centers often ignore the cooperation between distribution centers and share the distribution tasks and risks, resulting in waste of resources, low utilization rate and so on. Collaborative distribution maximizes the utilization efficiency of logistics resources such as personnel, materials, money, time, and so on, improves the response speed of logistics distribution and the level of logistics service, obtains the greatest social benefits, and can also reduce the duplication of construction of logistics facilities. Realize reasonable distribution of logistics facilities, and achieve social benefits such as alleviating traffic congestion and protecting environment. Therefore, it is of great significance to study cooperative distribution path for improving distribution efficiency and reducing distribution cost. Firstly, this paper discusses the research background and significance, analyzes the current research situation at home and abroad, and expounds the related theories of collaborative distribution and customer satisfaction. Secondly, through the analysis of the classical path optimization mathematical model and the mathematical realization process of customer satisfaction, the logistics collaborative distribution path optimization model based on customer satisfaction is established. When the model is established, the special distribution mode and the effectiveness of collaborative distribution are considered, and the influence of customer satisfaction on distribution selection is considered. Thirdly, the basic principles and advantages and disadvantages of genetic algorithm and ant colony algorithm are summarized, and the design idea and basic steps of genetic ant colony algorithm are given. Finally, the algorithm design of path optimization is described, and an example is given to verify the validity and feasibility of the model.
【学位授予单位】：河北工程大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F252;TP18
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