{"title":"Stochastic Variable Neighborhood Search for a Rotation Assignment Problem","authors":"Ziran Zheng","doi":"10.1145/3501409.3501522","DOIUrl":null,"url":null,"abstract":"In this paper, we deal with a type of rotation assignment problem motivated by a real-life training program, where a number of trainees are to be assigned to rotations within a planning horizon under a set of constraints. A major type of constraint stipulates that each trainee should perform a rotation in a range of consecutive time periods. Fairness of trainees being assigned to rotations and rest requests from trainees are also considered. We develop a stochastic neighborhood search algorithm for solving this problem. The algorithm uses an iterated stochastic neighborhood search framework with a simple acceptance criterion. The algorithm has no parameters and is very easy to implement. The approach is tested on a set of instances from real-life settings. We compare our approach with another neighborhood search procedure. The results show the effectiveness of our algorithm.","PeriodicalId":191106,"journal":{"name":"Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3501409.3501522","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we deal with a type of rotation assignment problem motivated by a real-life training program, where a number of trainees are to be assigned to rotations within a planning horizon under a set of constraints. A major type of constraint stipulates that each trainee should perform a rotation in a range of consecutive time periods. Fairness of trainees being assigned to rotations and rest requests from trainees are also considered. We develop a stochastic neighborhood search algorithm for solving this problem. The algorithm uses an iterated stochastic neighborhood search framework with a simple acceptance criterion. The algorithm has no parameters and is very easy to implement. The approach is tested on a set of instances from real-life settings. We compare our approach with another neighborhood search procedure. The results show the effectiveness of our algorithm.