{"title":"Minimizing Makespan in Semiresumable Case of Single-Machine Scheduling with an Availability Constraint","authors":"Ma Ying , Yang Shan-lin , Chu Cheng-bin","doi":"10.1016/S1874-8651(10)60018-X","DOIUrl":null,"url":null,"abstract":"<div><p>A single-machine scheduling problem with an unavailable period to minimize makespan is discussed in this article. The disrupted job is assumed to be semiresumable. It is shown that the relative worst-case error bound of the longest processing time (LPT) algorithm is α/2, where α is reprocess-ratio. Furthermore, an example is provided to show the tightness of this bound, and then a LPT-based heuristic is proposed. Computational results show that this heuristic is quite effective in finding an optimal or near-optimal solution. Effects of different parameters on this algorithm are also analyzed.</p></div>","PeriodicalId":101206,"journal":{"name":"Systems Engineering - Theory & Practice","volume":"29 4","pages":"Pages 128-134"},"PeriodicalIF":0.0000,"publicationDate":"2009-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1874-8651(10)60018-X","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Systems Engineering - Theory & Practice","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S187486511060018X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
A single-machine scheduling problem with an unavailable period to minimize makespan is discussed in this article. The disrupted job is assumed to be semiresumable. It is shown that the relative worst-case error bound of the longest processing time (LPT) algorithm is α/2, where α is reprocess-ratio. Furthermore, an example is provided to show the tightness of this bound, and then a LPT-based heuristic is proposed. Computational results show that this heuristic is quite effective in finding an optimal or near-optimal solution. Effects of different parameters on this algorithm are also analyzed.