海运物流场站—码头作业调度方法

发布时间：2018-03-02 11:40

本文选题：海运物流　切入点：场站—码头作业调度模型　出处：《哈尔滨工业大学》2015年硕士论文　论文类型：学位论文

【摘要】：伴随着全球经济一体化步伐的加快,世界各国间的贸易往来日益频繁,跨地域商品交易量大幅增长,海运物流作为当今国际贸易往来的重要交通枢纽直接影响和制约着我国的经济增长,然而现有的海运物流服务水平已经很难满足日益增长的需求。如何通过对海运物流终端节点场站、码头间的作业进行有效地调度以实现对集装箱进行快速操作的目标,是解决该问题的有效方法。集装箱是海运物流场站—码头作业调度的主要操作对象,如何在海运物流场站—码头有限资源的条件下,有效协调各部分资源之间的关系,缩短船舶在港口的等待时间,有效地提高海运物流场站—码头作业调度的服务水平是本文所需要解决的主要问题。针对该问题,本文提出了海运物流场站—码头作业调度计划方法。首先,针对海运物流场站、码头当中所具有的资源进行分析和定义,其中包括岸桥装卸服务资源的分析和定义,水平运输服务资源的分析和定义,场站装卸设备服务资源的分析和定义,场站堆存服务资源的分析和定义,在此基础上明确影响海运物流场站—码头作业调度问题的主要影响因素;其次,针对海运物流场站—码头作业调度问题进行深入研究,并且建立该问题各部分所对应的数学模型。考虑到海运物流场站—码头作业调度问题隶属于大规模组合优化的研究领域,使用传统的优化算法很难对此问题进行有效地求解,鉴于仿生智能优化算法对该类问题求解的良好表现,本文针对问题模型的离散性、动态性和多目标约束的特点对遗传算法和人工蜂群算法进行了有针对性的改进以适应对该问题模型的求解,并且进一步对两种算法的求解结果进行了对比,以证明模型的合理性和所提算法对问题的求解性能;最后,针对所建立的模型和所使用的算法搭建一个原型系统,对所建立的模型和所应用的算法的求解结果给出更加直观的表现形式。本文所搭建的原型系统针对海运物流场站—码头的具体实例进行设计,通过模型库、算法库和业务处理模块最后通过前端展示模块对问题求解结果、性能对比结果、优化效果进行可视化的直观展示。
[Abstract]:With the acceleration of the pace of global economic integration, trade exchanges between countries in the world are becoming more and more frequent, and the volume of cross-regional commodity transactions has increased substantially. As an important transportation hub of international trade, maritime logistics directly affects and restricts the economic growth of our country. However, the existing service level of maritime logistics has been difficult to meet the increasing demand. How to effectively schedule the operations between terminals and terminals to achieve the goal of rapid operation of containers. Container is the main operation object of marine logistics station-wharf operation scheduling, how to coordinate the relationship between each part of resources effectively under the condition of limited resources of marine logistics station-wharf, Shortening the waiting time of the ship in the port and effectively improving the service level of the seaborne logistics station-wharf operation scheduling are the main problems to be solved in this paper. In this paper, the scheduling method of marine logistics station-wharf operation is put forward. Firstly, the analysis and definition of the resources in the terminal, including the analysis and definition of the loading and unloading service resources of the shore bridge, are carried out. Analysis and definition of horizontal transportation service resources, analysis and definition of station-handling equipment service resources, analysis and definition of stowage service resources at yard stations, On this basis, it is clear that the main factors that affect the operation scheduling problem of maritime logistics station-wharf. Secondly, the paper makes a deep research on the operation scheduling problem of marine logistics station-wharf. Considering that the scheduling problem belongs to the research field of large-scale combinatorial optimization, it is difficult to solve the problem effectively by using the traditional optimization algorithm. In view of the good performance of the bionic intelligent optimization algorithm for solving this kind of problem, this paper aims at the discreteness of the problem model. The dynamic and multi-objective constraints have improved the genetic algorithm and artificial bee colony algorithm to adapt to the solution of the problem model, and further compared the results of the two algorithms. In order to prove the rationality of the model and the performance of the proposed algorithm to solve the problem. Finally, a prototype system is built for the established model and the algorithm used. In this paper, the prototype system is designed for the specific example of marine logistics station-wharf, through the model base, Finally, the algorithm library and business processing module display the result of solving the problem through the front-end display module, compare the results of performance, and visualize the optimization effect.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：U691.3;U695.2;TP18

【参考文献】