{"title":"LP-based working subsets for personnel scheduling: Evaluation and augmentation","authors":"M. Brusco, T. R. Johns, R. Venkataraman","doi":"10.1504/EJIE.2018.090614","DOIUrl":null,"url":null,"abstract":"This paper evaluates the efficacy of LP-based working subsets for generalised set-covering formulations of personnel scheduling problems and presents a nearest-neighbour augmentation procedure for improving performance. Three experimental studies were completed in the evaluation process. In the first study, the LP-based working subset was sufficient to yield an optimal shift scheduling solution for 85% of the 24,300 test problems and the nearest-neighbour augmentation improved the percentage of optimal solutions to over 98%. The second study focused on more complex cyclic shift scheduling environments that permitted shift length, meal break and relief break flexibility. The adequacy of LP-based working subsets was supported by the provision of optimal shift scheduling solutions for 185 of 189 (98%) of the test problems. The third study examined a challenging tour scheduling environment for which globally-optimal benchmarks are not available. The superiority of the augmented LP-based working subset procedure was nevertheless evident, as it yielded better results than the (non-augmented) LP-based working subset for 92% of the test problems despite being constrained to only 40% of the allowed computation time for the non-augmented subsets. [Received 24 April 2017; Revised 25 August 2017; Revised 17 September 2017; Accepted 6 December 2017]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":"12 1","pages":"175-198"},"PeriodicalIF":1.9000,"publicationDate":"2018-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2018.090614","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Industrial Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1504/EJIE.2018.090614","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 0
Abstract
This paper evaluates the efficacy of LP-based working subsets for generalised set-covering formulations of personnel scheduling problems and presents a nearest-neighbour augmentation procedure for improving performance. Three experimental studies were completed in the evaluation process. In the first study, the LP-based working subset was sufficient to yield an optimal shift scheduling solution for 85% of the 24,300 test problems and the nearest-neighbour augmentation improved the percentage of optimal solutions to over 98%. The second study focused on more complex cyclic shift scheduling environments that permitted shift length, meal break and relief break flexibility. The adequacy of LP-based working subsets was supported by the provision of optimal shift scheduling solutions for 185 of 189 (98%) of the test problems. The third study examined a challenging tour scheduling environment for which globally-optimal benchmarks are not available. The superiority of the augmented LP-based working subset procedure was nevertheless evident, as it yielded better results than the (non-augmented) LP-based working subset for 92% of the test problems despite being constrained to only 40% of the allowed computation time for the non-augmented subsets. [Received 24 April 2017; Revised 25 August 2017; Revised 17 September 2017; Accepted 6 December 2017]
期刊介绍:
EJIE is an international journal aimed at disseminating the latest developments in all areas of industrial engineering, including information and service industries, ergonomics and safety, quality management as well as business and strategy, and at bridging the gap between theory and practice.