摘要
以WOS和CNKI数据库为基础,利用VOSviewer对检索出的494篇文献进行共词聚类分析,得出码头设备资源的调度是自动化集装箱码头领域近年来的热点。按照设备资源的种类数量进行分类综述,提出未来的研究方向。研究结果表明:多数文献建立了时间最小化,装卸效率最高的目标函数,但近年环境问题日益受到关注,能耗等相关环境内容加入到目标中考虑,形成多目标函数问题;前期的文献主要针对单一的装卸工艺进行研究,并取得了较多成果,在今后研究中,应结合自动化集装箱码头的特点,将研究重心转移到自动化集装箱码头的混合工艺上;多数文献只针对单装或单卸模式进行研究,而忽略了双周期策略的应用;多数文献主要研究确定情况下设备资源的调度问题,随着研究的深入,不确定情况下的调度问题将会成为未来研究的重点。随着码头装卸量的不断上升,普通的智能算法求解效率逐渐降低,未来可以开发更多快速的,系统化的求解算法。
Based on two major databases,WOS and CNKI,the 494 documents searched were analyzed by using VOSviewer for co-word clustering,and the conclusion is that the scheduling of terminal equipment resources is a hot issue in the field of automated container terminals in recent years;the review is categorized according to the types of equipment resources,with the future research direction pointed out.The research results show that most literatures have established an objective function that minimizes time and have the highest loading and unloading efficiency.However,as energy consumption issues receive more and more attention,energy consumption and other related environmental content should be added to the target to form a multi-objective function.The preliminary literature mainly focuses on single loading and unloading process,and has achieved a lot of results.In the future,the research focus should be shifted to the hybrid process,taking into account the characteristics of automated container terminals.Most literatures only study the single loading or single unloading mode,and application of the dual-cycle strategy is ignored;most literatures mainly study the scheduling problem of equipment resources under certain conditions.As the research further develops,the scheduling problem under uncertain conditions will become the focus of future research.With the increase of loading and unloading volumes,the solving efficiency of ordinary intelligent algorithms is gradually reduced.In the future,more rapid and systematic solving algorithms can be developed.
作者
初良勇
周于佩
梁冬
许小卫
CHU Liangyong;ZHOU Yupei;LIANG Dong;XU Xiaowei(Navigation College,Jimei University,Xiamen 361021,China;Shipping Research Institute of Fujian Province,Xiamen 361021,China;School of Management Science and Engineering,Anhui Universtiy of Finance and Economics,Bengbu 233000,China)
出处
《集美大学学报(自然科学版)》
CAS
2023年第3期230-238,共9页
Journal of Jimei University:Natural Science
基金
国家重点研发计划项目(2017YFC0805309)
福建省自然科学基金项目(2021J01820)
福建省教育厅项目(JAT190294
JAT190292)。
关键词
设备资源
调度优化
自动化集装箱码头
水路运输
equipment resources
scheduling optimization
automated container terminal
literature review
waterway transportation