{"title":"Simple, Yet Fast and Effective Two-Phase Method for Nurse Rostering","authors":"F. Guessoum, S. Haddadi, E. Gattal","doi":"10.1080/01966324.2019.1570882","DOIUrl":null,"url":null,"abstract":"SYNOPTIC ABSTRACT The nurse rostering problem is to create a day-to-day shift assignment of each nurse subject to a predefined set of constraints. Based on simple ideas, a two-phase method is suggested. The first phase consists of applying a generic variable-fixing heuristic. As a result, a very small and sparse-reduced problem is obtained. In the second phase, the reduced problem is solved by utilizing a general-purpose MIP solver. The proposed method is tested on NSPLib dataset, and the results obtained show that it is capable of identifying high quality solutions. When compared with recently developed methods, it turns out to be the fastest.","PeriodicalId":35850,"journal":{"name":"American Journal of Mathematical and Management Sciences","volume":"39 1","pages":"1 - 19"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/01966324.2019.1570882","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Mathematical and Management Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/01966324.2019.1570882","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Business, Management and Accounting","Score":null,"Total":0}
引用次数: 7
Abstract
SYNOPTIC ABSTRACT The nurse rostering problem is to create a day-to-day shift assignment of each nurse subject to a predefined set of constraints. Based on simple ideas, a two-phase method is suggested. The first phase consists of applying a generic variable-fixing heuristic. As a result, a very small and sparse-reduced problem is obtained. In the second phase, the reduced problem is solved by utilizing a general-purpose MIP solver. The proposed method is tested on NSPLib dataset, and the results obtained show that it is capable of identifying high quality solutions. When compared with recently developed methods, it turns out to be the fastest.
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