Zhiyuan Yang , Miaomiao Wang , Shuaian Wang , Lu Zhen
{"title":"优化连续泊位分配、时变码头起重机和堆场分配","authors":"Zhiyuan Yang , Miaomiao Wang , Shuaian Wang , Lu Zhen","doi":"10.1016/j.trb.2025.103317","DOIUrl":null,"url":null,"abstract":"<div><div>Efficient container terminal operations depend on the coordinated use of three key resources: berths, quay cranes (QCs), and yard space. Decisions involving these components are highly interrelated. Berth allocation affects QC scheduling, which in turn influences yard-side transport. However, the majority of the literature treat these problems separately or under simplifying assumptions such as discrete berth allocation, time-invariant QC allocation, or omission of yard assignment. To the best of our known, this paper is the first to formulate a unified continuous-time optimization model that integrates continuous berth allocation, time-variant QC scheduling, and yard space assignment. To solve our proposed comprehensive decision model, we develop an exact algorithm and accelerate this by designing some novel valid inequalities and M-tightening techniques. The algorithmic efficiency and the benefits of considering the aforementioned decision features are validated through computational experiments. In addition, sensitivity analyses are conducted to derive potentially useful managerial insights.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"200 ","pages":"Article 103317"},"PeriodicalIF":6.3000,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimizing continuous-time berth allocation, time-variant quay crane and yard assignment\",\"authors\":\"Zhiyuan Yang , Miaomiao Wang , Shuaian Wang , Lu Zhen\",\"doi\":\"10.1016/j.trb.2025.103317\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Efficient container terminal operations depend on the coordinated use of three key resources: berths, quay cranes (QCs), and yard space. Decisions involving these components are highly interrelated. Berth allocation affects QC scheduling, which in turn influences yard-side transport. However, the majority of the literature treat these problems separately or under simplifying assumptions such as discrete berth allocation, time-invariant QC allocation, or omission of yard assignment. To the best of our known, this paper is the first to formulate a unified continuous-time optimization model that integrates continuous berth allocation, time-variant QC scheduling, and yard space assignment. To solve our proposed comprehensive decision model, we develop an exact algorithm and accelerate this by designing some novel valid inequalities and M-tightening techniques. The algorithmic efficiency and the benefits of considering the aforementioned decision features are validated through computational experiments. In addition, sensitivity analyses are conducted to derive potentially useful managerial insights.</div></div>\",\"PeriodicalId\":54418,\"journal\":{\"name\":\"Transportation Research Part B-Methodological\",\"volume\":\"200 \",\"pages\":\"Article 103317\"},\"PeriodicalIF\":6.3000,\"publicationDate\":\"2025-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Research Part B-Methodological\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0191261525001663\",\"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 B-Methodological","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0191261525001663","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
Optimizing continuous-time berth allocation, time-variant quay crane and yard assignment
Efficient container terminal operations depend on the coordinated use of three key resources: berths, quay cranes (QCs), and yard space. Decisions involving these components are highly interrelated. Berth allocation affects QC scheduling, which in turn influences yard-side transport. However, the majority of the literature treat these problems separately or under simplifying assumptions such as discrete berth allocation, time-invariant QC allocation, or omission of yard assignment. To the best of our known, this paper is the first to formulate a unified continuous-time optimization model that integrates continuous berth allocation, time-variant QC scheduling, and yard space assignment. To solve our proposed comprehensive decision model, we develop an exact algorithm and accelerate this by designing some novel valid inequalities and M-tightening techniques. The algorithmic efficiency and the benefits of considering the aforementioned decision features are validated through computational experiments. In addition, sensitivity analyses are conducted to derive potentially useful managerial insights.
期刊介绍:
Transportation Research: Part B publishes papers on all methodological aspects of the subject, particularly those that require mathematical analysis. The general theme of the journal is the development and solution of problems that are adequately motivated to deal with important aspects of the design and/or analysis of transportation systems. Areas covered include: traffic flow; design and analysis of transportation networks; control and scheduling; optimization; queuing theory; logistics; supply chains; development and application of statistical, econometric and mathematical models to address transportation problems; cost models; pricing and/or investment; traveler or shipper behavior; cost-benefit methodologies.