Optimising truck arrival management and number of service gates at container terminals

IF 2 Q3 BUSINESS
C. C. Minh, N. Noi
{"title":"Optimising truck arrival management and number of service gates at container terminals","authors":"C. C. Minh, N. Noi","doi":"10.1108/mabr-08-2021-0060","DOIUrl":null,"url":null,"abstract":"PurposeTruck appointment systems have been applied in critical container ports in the United States due to their potential to improve handling operations. This paper aims to develop a truck appointment system to optimise the total cost experiencing at the entrance of container terminals by managing truck arrivals and the number of service gates satisfying a given level of service.Design/methodology/approachThe approximation of Mt/G/nt queuing model is applied and integrated into a cost optimisation model to identify (1) the number of arrival trucks allowed at each time slot and (2) the number of service gates operating at each time slot that ensure the average waiting time is less than a designated time threshold. The optimisation model is solved by the Genetic Algorithm and tested with a case study. Its effectiveness is identified by comparing the model's outcomes with observed data and other recent studies.FindingsThe results indicate that the developed truck appointment system can provide more than threefold and twofold reductions of the total cost experiencing at the terminal entrance compared to the actual data and results from previous research, respectively.Originality/valueThe proposed approach provides applicably coordinated truck plans and operating service gates efficiently to decrease congestion, emission and expenses.","PeriodicalId":43865,"journal":{"name":"Maritime Business Review","volume":" ","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Maritime Business Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/mabr-08-2021-0060","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 4

Abstract

PurposeTruck appointment systems have been applied in critical container ports in the United States due to their potential to improve handling operations. This paper aims to develop a truck appointment system to optimise the total cost experiencing at the entrance of container terminals by managing truck arrivals and the number of service gates satisfying a given level of service.Design/methodology/approachThe approximation of Mt/G/nt queuing model is applied and integrated into a cost optimisation model to identify (1) the number of arrival trucks allowed at each time slot and (2) the number of service gates operating at each time slot that ensure the average waiting time is less than a designated time threshold. The optimisation model is solved by the Genetic Algorithm and tested with a case study. Its effectiveness is identified by comparing the model's outcomes with observed data and other recent studies.FindingsThe results indicate that the developed truck appointment system can provide more than threefold and twofold reductions of the total cost experiencing at the terminal entrance compared to the actual data and results from previous research, respectively.Originality/valueThe proposed approach provides applicably coordinated truck plans and operating service gates efficiently to decrease congestion, emission and expenses.
优化卡车到达管理和集装箱码头服务门数量
目的卡车预约系统已应用于美国的关键集装箱港口,因为它们有可能改善处理操作。本文旨在开发一个卡车预约系统,通过管理卡车到达和满足给定服务水平的服务门的数量来优化集装箱码头入口处的总成本体验。设计/方法/方法采用Mt/G/nt的近似排队模型,并将其整合到成本优化模型中,以确定(1)每个时点允许到达的卡车数量,以及(2)每个时点运行的服务门数量,以确保平均等待时间少于指定的时间阈值。采用遗传算法对优化模型进行求解,并通过实例进行了验证。通过将模型结果与观测数据和其他近期研究进行比较,可以确定其有效性。结果表明,与之前的研究结果和实际数据相比,开发的卡车预约系统可以将终端入口的总成本分别降低三倍和两倍以上。独创性/价值提出的方法提供适用的协调卡车计划和运营服务门,有效地减少拥堵,排放和费用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
4.80
自引率
0.00%
发文量
19
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信