集装箱码头集卡调度优化研究

发布时间：2018-06-24 08:52

本文选题：集卡调度 + 堆场存储安排　；参考：《深圳大学》2017年硕士论文

【摘要】：集装箱运输开启了现代物流发展的新篇章,是现代物流发展的一个重要标志。然而,逐年增长的集装箱吞吐量以及船舶大型化的发展趋势也对我国各集装箱码头提出了新的要求,同时,进一步加剧了各个集装箱码头之间的竞争。集装箱码头只有致力于提高自身的服务水平、运营效率,才能在新一轮的竞争中不被淘汰。在集装箱码头作业过程中,集卡作为一种重要的基础工具,具有使用量大、灵活、成本相对较低等特点,在港岸和堆场之间起着运输集装箱的重要作用。同时,作为集装箱的存储、转运基地,堆场对集卡调度方案的设计有着重要的影响。本文对集卡的调度问题进行了研究,旨在缩短集装箱的装卸时间,提高港口集装箱的周转效率,从而实现港口资源的优化配置,增强港口的竞争力。基于此,本文在国家自然科学基金(71571120,71271140,71471158)及广东省自然科学基金(2016A030310074)的资助下开展了如下研究:首先,本文综合考虑了堆场存储空间动态变化的特点,包括堆场存储位置数量的变化以及存储位置的变化,提出了“先进后出”、“先出后进”的集装箱运输策略,并探讨了不同策略的使用条件,建立了基于堆场可用存储位置动态变化的集卡调度模型。其次,对集卡调度问题进行了进一步拓展,研究了采用协同调度策略时集装箱码头的集卡调度问题,基于“重进重出”的思想,提出了进出口运输联合的集卡调度方案,建立了基于协同调度策略的集卡调度模型。协同调度策略不是把集卡看成独立的个体,而是看成可以互相协助的一个群集。该策略主要利用了集卡相互协作作业的优势,有效的减少了集卡调度过程中的空载率,从而提高了集卡调度的效率。最后,鉴于所建立的集卡调度模型在求解上属于NP-hard问题,本文采用了粒子群优化算法及其改进算法对此问题进行优化求解。通过建立映射关系,保证了粒子群优化算法对此问题的适用性。通过算例分析了模型和算法的性能,并和CPLEX仿真优化结果进行了对比分析,结果显示本文所提出的模型对解决集装箱码头集卡调度问题具有一定的指导意义。
[Abstract]:Container transportation opens a new chapter of modern logistics development and is an important symbol of modern logistics development. However, the annual increase of container throughput and the trend of large-scale development of ships also put forward new requirements for each container terminal in China, at the same time, it further intensifies the competition among various container terminals. Container terminal can not be eliminated in the new round of competition only by devoting itself to improving its service level and operating efficiency. In the process of container terminal operation, as an important basic tool, the card has the characteristics of large usage, flexibility and relatively low cost, which plays an important role in the transportation of containers between port and yard. At the same time, as container storage, transfer base, yard has an important impact on the design of card scheduling scheme. In this paper, the scheduling problem of the card is studied in order to shorten the loading and unloading time of the container, improve the turnover efficiency of the port container, realize the optimal allocation of the port resources and enhance the competitiveness of the port. Based on this, this paper has carried out the following research with the support of the National Natural Science Foundation of China (71571120 / 71271140 / 71471158) and the Natural Science Foundation of Guangdong Province (2016A030310074). Including the quantity change of storage location and the change of storage location, the container transportation strategy of "first-out" and "first-out" is put forward, and the use conditions of different strategies are discussed. A card scheduling model based on the dynamic change of the available storage location in the yard is established. Secondly, the card gathering scheduling problem is further expanded, and the card gathering scheduling problem of container terminal is studied when the cooperative scheduling strategy is adopted. Based on the idea of "re-entry and re-output", the paper puts forward a combined card-gathering scheduling scheme for import and export transportation. A card scheduling model based on cooperative scheduling strategy is established. The cooperative scheduling strategy does not treat the card as an individual, but as a cluster that can assist each other. The strategy makes use of the advantages of the cooperation between the cards and effectively reduces the no-load rate in the process of card scheduling so as to improve the efficiency of card scheduling. Finally, in view of the NP-hard problem of the set card scheduling model, the particle swarm optimization algorithm and its improved algorithm are used to solve the problem. By establishing mapping relation, the applicability of particle swarm optimization algorithm to this problem is ensured. The performance of the model and algorithm is analyzed by an example, and compared with the results of CPLEX simulation. The results show that the proposed model has a certain guiding significance to solve the container terminal card collection scheduling problem.
【学位授予单位】：深圳大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U691.3

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