{"title":"Disruption-responsive berth allocation and quay crane scheduling with inter-terminal collaboration","authors":"Hongxing Zheng , Zhaoyang Wang , Lingxiao Wu","doi":"10.1016/j.eswa.2025.129776","DOIUrl":null,"url":null,"abstract":"<div><div>Container terminal operations frequently encounter disruptions, including delays, extended handling times, and unscheduled vessel arrivals, all of which necessitate intelligent rescheduling strategies to maintain operational efficiency. This study investigates the integrated problem of disruption-responsive berth allocation and quay crane (QC) scheduling, explicitly considering vessel gathering status and incorporating inter-terminal shifting (ITS) and reassignment to terminals different from its originally designated one (RT) as adaptive response strategies to mitigate these disruptions. A rescheduling model is developed to minimize associated costs. To efficiently solve large-scale problems, an adaptive large neighborhood search (ALNS)-based heuristic is proposed. The effectiveness of the proposed scheme is validated through comparative experiments involving three alternative schemes, highlighting its superior performance. Furthermore, algorithm comparison experiments are conducted to verify the robustness of parameter settings. Computational results demonstrate that the proposed model and algorithm achieve high efficiency and solution quality. Additionally, sensitivity analysis reveals that neglecting vessel gathering status leads to substantial cost increases, particularly in large-scale operations. The integration of ITS and RT proves to be an effective strategy for mitigating disruptions, enhancing scheduling flexibility, and improving operational performance.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"298 ","pages":"Article 129776"},"PeriodicalIF":7.5000,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Expert Systems with Applications","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0957417425033913","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Container terminal operations frequently encounter disruptions, including delays, extended handling times, and unscheduled vessel arrivals, all of which necessitate intelligent rescheduling strategies to maintain operational efficiency. This study investigates the integrated problem of disruption-responsive berth allocation and quay crane (QC) scheduling, explicitly considering vessel gathering status and incorporating inter-terminal shifting (ITS) and reassignment to terminals different from its originally designated one (RT) as adaptive response strategies to mitigate these disruptions. A rescheduling model is developed to minimize associated costs. To efficiently solve large-scale problems, an adaptive large neighborhood search (ALNS)-based heuristic is proposed. The effectiveness of the proposed scheme is validated through comparative experiments involving three alternative schemes, highlighting its superior performance. Furthermore, algorithm comparison experiments are conducted to verify the robustness of parameter settings. Computational results demonstrate that the proposed model and algorithm achieve high efficiency and solution quality. Additionally, sensitivity analysis reveals that neglecting vessel gathering status leads to substantial cost increases, particularly in large-scale operations. The integration of ITS and RT proves to be an effective strategy for mitigating disruptions, enhancing scheduling flexibility, and improving operational performance.
期刊介绍:
Expert Systems With Applications is an international journal dedicated to the exchange of information on expert and intelligent systems used globally in industry, government, and universities. The journal emphasizes original papers covering the design, development, testing, implementation, and management of these systems, offering practical guidelines. It spans various sectors such as finance, engineering, marketing, law, project management, information management, medicine, and more. The journal also welcomes papers on multi-agent systems, knowledge management, neural networks, knowledge discovery, data mining, and other related areas, excluding applications to military/defense systems.