{"title":"Integrated optimization of supplier selection and service scheduling in cloud manufacturing environment","authors":"Sisi Lin, Y. Laili, Yongliang Luo","doi":"10.1109/UV.2018.8642124","DOIUrl":null,"url":null,"abstract":"Cloud Manufacturing environment enables enterprises to share their resources together for rental profits and customized production. The fact that most manufacturing devices are organized and controlled in a particular production line hinders the flexible use of the corresponding services in a cloud platform. Therefore, the collaborative selection of upper layer suppliers and the underlying manufacturing services is of great importance, but rarely considered. To address the problem, a two-layer integrated model of supplier selection and service scheduling is proposed to provide feasible solutions for different kinds of production requirements. The decomposition-based multi-objective evolutionary algorithm, i.e., MOEA/D, is applied to minimize the production time, the rental cost and the transportation cost for producing a customized product. We empirically demonstrate that the integrated optimization way is more efficient than the original two-step decision way in practice.","PeriodicalId":110658,"journal":{"name":"2018 4th International Conference on Universal Village (UV)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 4th International Conference on Universal Village (UV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UV.2018.8642124","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Cloud Manufacturing environment enables enterprises to share their resources together for rental profits and customized production. The fact that most manufacturing devices are organized and controlled in a particular production line hinders the flexible use of the corresponding services in a cloud platform. Therefore, the collaborative selection of upper layer suppliers and the underlying manufacturing services is of great importance, but rarely considered. To address the problem, a two-layer integrated model of supplier selection and service scheduling is proposed to provide feasible solutions for different kinds of production requirements. The decomposition-based multi-objective evolutionary algorithm, i.e., MOEA/D, is applied to minimize the production time, the rental cost and the transportation cost for producing a customized product. We empirically demonstrate that the integrated optimization way is more efficient than the original two-step decision way in practice.