{"title":"Anchored rescheduling problem with non-availability periods","authors":"","doi":"10.1016/j.orl.2024.107201","DOIUrl":null,"url":null,"abstract":"<div><div>A set of jobs with precedence constraints is given along with a baseline schedule, resulting from the first-stage decision of a robust two-stage scheduling problem. Non-availability periods caused by unpredicted disruptions prevent jobs from being executed on certain time intervals, thus requiring rescheduling. The anchored rescheduling problem with non-availability periods is to find a schedule maximizing the number of so-called anchored jobs whose starting times remain close to the baseline schedule. It is shown to be solvable in polynomial time.</div></div>","PeriodicalId":54682,"journal":{"name":"Operations Research Letters","volume":null,"pages":null},"PeriodicalIF":0.8000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Operations Research Letters","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167637724001378","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
A set of jobs with precedence constraints is given along with a baseline schedule, resulting from the first-stage decision of a robust two-stage scheduling problem. Non-availability periods caused by unpredicted disruptions prevent jobs from being executed on certain time intervals, thus requiring rescheduling. The anchored rescheduling problem with non-availability periods is to find a schedule maximizing the number of so-called anchored jobs whose starting times remain close to the baseline schedule. It is shown to be solvable in polynomial time.
期刊介绍：
Operations Research Letters is committed to the rapid review and fast publication of short articles on all aspects of operations research and analytics. Apart from a limitation to eight journal pages, quality, originality, relevance and clarity are the only criteria for selecting the papers to be published. ORL covers the broad field of optimization, stochastic models and game theory. Specific areas of interest include networks, routing, location, queueing, scheduling, inventory, reliability, and financial engineering. We wish to explore interfaces with other fields such as life sciences and health care, artificial intelligence and machine learning, energy distribution, and computational social sciences and humanities. Our traditional strength is in methodology, including theory, modelling, algorithms and computational studies. We also welcome novel applications and concise literature reviews.
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