{"title":"Multi-objective constraint optimization in mail-order pharmacy automated distribution system","authors":"T. Miyamoto, N. Ueno, D. Li, S. Yoon","doi":"10.1109/IEEM.2016.7797834","DOIUrl":null,"url":null,"abstract":"In this research, we study a scheduling problem in mail-order pharmacy automated distribution (MOPAD) system. In MOPAD scheduling, two kinds of objective: the collation delay (CD) and makespan, should be considered and in the previous study of some of authors three kinds of genetic algorithms (GA) are applied and evaluated. In this paper, we apply constraint programming (CP) for the scheduling problem. We proposed a CP formulation of the problem and evaluated through computational experiments. The results show that the proposed method is effective for small-scale problem but further study is required to compare with GA methods in large-scale problems.","PeriodicalId":114906,"journal":{"name":"2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEM.2016.7797834","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 research, we study a scheduling problem in mail-order pharmacy automated distribution (MOPAD) system. In MOPAD scheduling, two kinds of objective: the collation delay (CD) and makespan, should be considered and in the previous study of some of authors three kinds of genetic algorithms (GA) are applied and evaluated. In this paper, we apply constraint programming (CP) for the scheduling problem. We proposed a CP formulation of the problem and evaluated through computational experiments. The results show that the proposed method is effective for small-scale problem but further study is required to compare with GA methods in large-scale problems.