中文核心期刊
CSCD来源期刊
中国科技核心期刊
RCCSE中国核心学术期刊

重庆交通大学学报(自然科学版) ›› 2023, Vol. 42 ›› Issue (7): 120-127.DOI: 10.3969/j.issn.1674-0696.2023.07.16

• 交通基础设施工程 • 上一篇    

确定任务视角下集装箱堆场箱位分配研究

郑云峰,刘瑞麟,饶本顺,周校彬,张国庆   

  1. (大连海事大学 航海学院,辽宁 大连 116026)
  • 收稿日期:2021-07-13 修回日期:2021-10-19 发布日期:2023-09-08
  • 作者简介:郑云峰(1974—),男,黑龙江绥棱人,副教授,博士,主要从事交通运输工程方面的研究。E-mail:20061084@dlmu.edu.cn 通信作者:刘瑞麟(1998—),男,河南驻马店人,硕士,主要从事交通运输工程方面的研究。E-mail:led0zeppelin@163.com
  • 基金资助:
    国家自然科学基金项目(51909018)

Location Allocation of Container Yard from the Perspective of Determining Tasks

ZHENG Yunfeng, LIU Ruilin, RAO Benshun, ZHOU Xiaobin, ZHANG Guoqing   

  1. (Navigation College, Dalian Maritime University, Dalian 116026, Liaoning, China)
  • Received:2021-07-13 Revised:2021-10-19 Published:2023-09-08

摘要: 为了合理分配堆场资源和提高码头工作效率,针对集装箱堆场箱位分配问题进行研究。考虑码头到港船舶目的地、时间、箱重等因素,以场桥的行车成本和翻箱成本之和最低为目标,建立堆场箱位分配模型。为增强算法的全局搜索能力,基于确定任务视角,将贝位选择和贝内排箱过程看作一个整体,设计一种在整个区域内搜索排箱位置的遗传算法对模型进行求解,得到具体箱位调度分配方案。通过仿真验证所提出算法的有效性,并与Yalmip软件对比,求解不同规模的算例,验证算法的性能。结果表明:该算法能够有效解决实际生产作业中箱位分配的问题,并在求解大规模算例时也能在较短时间给出较优解。

关键词: 交通运输工程;箱位分配;分区域规划;遗传算法;贝位选择;贝内排箱

Abstract: In order to allocate yard resources reasonably and improve the working efficiency of terminals, the allocation of container slots in container yards was studied. Considering the factors such as the destination, time, container weight of ships arriving at the dock, a container allocation model of the yard was established, with the goal of minimizing the sum of the driving cost and the container turnover cost of the yard bridge. In order to enhance the global search ability of the algorithm, based on the view of determining tasks, the process of bay selection and box arranglment in bay was regarded as a whole, a genetic algorithm for searching the box arrangement position in the whole region was designed to solve the model and the specific box location scheduling allocation scheme was obtained. The effectiveness of the proposed algorithm was verified by simulation and compared with Yalmip software. Examples of different scales were solved to verify the performance of the proposed algorithm. The results show that the proposed algorithm can effectively solve the problem of storage space allocation in actual production operation and can also provide a better solution in a short time when solving large-scale examples.

Key words: traffic and transportation engineering; location allocation; subregional planning; genetic algorithm; selection of bay; box arranglment in bay

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