{"title":"模糊多准则决策方法在机器人柔性装配单元动态调度中的应用","authors":"K. Abd, K. Abhary, R. Marian","doi":"10.1109/IEEM.2014.7058664","DOIUrl":null,"url":null,"abstract":"This paper is devoted to the application of the developed approach presented in Part I, to demonstrate its capability in tackling real-world MCDM problems. In this paper, a hypothetical case study of robotic flexible assembly cells (RFACs) is considered, to solve multi-objective optimization problems for dynamic scheduling. In order to find the optimal solution, a fuzzy decision support system (FDSS) is applied and built using the fuzzy logic toolbox in MATLAB software. The FDSS combines multi-objective functions in one performance measure named a multiple performance characteristics index (MPCI). The analysis results show that the developed approach is practical, works in RFACs setting, and deal with imprecise and uncertain information.","PeriodicalId":318405,"journal":{"name":"2014 IEEE International Conference on Industrial Engineering and Engineering Management","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Application of a fuzzy multi-criteria decision-making approach for dynamic scheduling in robotic flexible assembly cells\",\"authors\":\"K. Abd, K. Abhary, R. Marian\",\"doi\":\"10.1109/IEEM.2014.7058664\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper is devoted to the application of the developed approach presented in Part I, to demonstrate its capability in tackling real-world MCDM problems. In this paper, a hypothetical case study of robotic flexible assembly cells (RFACs) is considered, to solve multi-objective optimization problems for dynamic scheduling. In order to find the optimal solution, a fuzzy decision support system (FDSS) is applied and built using the fuzzy logic toolbox in MATLAB software. The FDSS combines multi-objective functions in one performance measure named a multiple performance characteristics index (MPCI). The analysis results show that the developed approach is practical, works in RFACs setting, and deal with imprecise and uncertain information.\",\"PeriodicalId\":318405,\"journal\":{\"name\":\"2014 IEEE International Conference on Industrial Engineering and Engineering Management\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE International Conference on Industrial Engineering and Engineering Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEEM.2014.7058664\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Conference on Industrial Engineering and Engineering Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEM.2014.7058664","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of a fuzzy multi-criteria decision-making approach for dynamic scheduling in robotic flexible assembly cells
This paper is devoted to the application of the developed approach presented in Part I, to demonstrate its capability in tackling real-world MCDM problems. In this paper, a hypothetical case study of robotic flexible assembly cells (RFACs) is considered, to solve multi-objective optimization problems for dynamic scheduling. In order to find the optimal solution, a fuzzy decision support system (FDSS) is applied and built using the fuzzy logic toolbox in MATLAB software. The FDSS combines multi-objective functions in one performance measure named a multiple performance characteristics index (MPCI). The analysis results show that the developed approach is practical, works in RFACs setting, and deal with imprecise and uncertain information.