{"title":"不确定条件下自动化集装箱码头的堆场模板生成","authors":"Mingzhong Huang , Junliang He , Hang Yu , Yu Wang","doi":"10.1016/j.tre.2024.103851","DOIUrl":null,"url":null,"abstract":"<div><div>This paper addresses yard template generation problem in automated container terminals when the vessel arrival schedule is uncertain. Since the yard is central to terminal operations, yard management directly affects the efficiency of most equipment. Yard template functions as a tactical-level yard management strategy, allocating yard space to vessels that call at the port on a weekly basis. By analyzing the operational requirements of the various equipment, a yard template is developed in which the stack is the decision unit. Since the yard template will be in operation for an extended period of time, it is critical to account for potential uncertainty. This allows the yard template to effectively manage the yard throughout its duration. Accordingly, a two-stage stochastic programming model is formulated to generate yard template under uncertainty. An improved Benders decomposition algorithm with multiple acceleration strategies is designed to solve the proposed model. The efficiency of the proposed algorithm is validated by numerical experiments. Moreover, some management insights are obtained, such as the impact of uncertain vessel arrival schedule on stack-based yard template and a comparative analysis of stacking strategies in the context of uncertainty.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"193 ","pages":"Article 103851"},"PeriodicalIF":8.3000,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Stack-based yard template generation in automated container terminals under uncertainty\",\"authors\":\"Mingzhong Huang , Junliang He , Hang Yu , Yu Wang\",\"doi\":\"10.1016/j.tre.2024.103851\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This paper addresses yard template generation problem in automated container terminals when the vessel arrival schedule is uncertain. Since the yard is central to terminal operations, yard management directly affects the efficiency of most equipment. Yard template functions as a tactical-level yard management strategy, allocating yard space to vessels that call at the port on a weekly basis. By analyzing the operational requirements of the various equipment, a yard template is developed in which the stack is the decision unit. Since the yard template will be in operation for an extended period of time, it is critical to account for potential uncertainty. This allows the yard template to effectively manage the yard throughout its duration. Accordingly, a two-stage stochastic programming model is formulated to generate yard template under uncertainty. An improved Benders decomposition algorithm with multiple acceleration strategies is designed to solve the proposed model. The efficiency of the proposed algorithm is validated by numerical experiments. Moreover, some management insights are obtained, such as the impact of uncertain vessel arrival schedule on stack-based yard template and a comparative analysis of stacking strategies in the context of uncertainty.</div></div>\",\"PeriodicalId\":49418,\"journal\":{\"name\":\"Transportation Research Part E-Logistics and Transportation Review\",\"volume\":\"193 \",\"pages\":\"Article 103851\"},\"PeriodicalIF\":8.3000,\"publicationDate\":\"2024-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Research Part E-Logistics and Transportation Review\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1366554524004423\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part E-Logistics and Transportation Review","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1366554524004423","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
Stack-based yard template generation in automated container terminals under uncertainty
This paper addresses yard template generation problem in automated container terminals when the vessel arrival schedule is uncertain. Since the yard is central to terminal operations, yard management directly affects the efficiency of most equipment. Yard template functions as a tactical-level yard management strategy, allocating yard space to vessels that call at the port on a weekly basis. By analyzing the operational requirements of the various equipment, a yard template is developed in which the stack is the decision unit. Since the yard template will be in operation for an extended period of time, it is critical to account for potential uncertainty. This allows the yard template to effectively manage the yard throughout its duration. Accordingly, a two-stage stochastic programming model is formulated to generate yard template under uncertainty. An improved Benders decomposition algorithm with multiple acceleration strategies is designed to solve the proposed model. The efficiency of the proposed algorithm is validated by numerical experiments. Moreover, some management insights are obtained, such as the impact of uncertain vessel arrival schedule on stack-based yard template and a comparative analysis of stacking strategies in the context of uncertainty.
期刊介绍:
Transportation Research Part E: Logistics and Transportation Review is a reputable journal that publishes high-quality articles covering a wide range of topics in the field of logistics and transportation research. The journal welcomes submissions on various subjects, including transport economics, transport infrastructure and investment appraisal, evaluation of public policies related to transportation, empirical and analytical studies of logistics management practices and performance, logistics and operations models, and logistics and supply chain management.
Part E aims to provide informative and well-researched articles that contribute to the understanding and advancement of the field. The content of the journal is complementary to other prestigious journals in transportation research, such as Transportation Research Part A: Policy and Practice, Part B: Methodological, Part C: Emerging Technologies, Part D: Transport and Environment, and Part F: Traffic Psychology and Behaviour. Together, these journals form a comprehensive and cohesive reference for current research in transportation science.