{"title":"基于直觉模糊集的制造业虚拟企业合作伙伴选择","authors":"Bin Huang, Liang Chen","doi":"10.1504/IJMTM.2014.066694","DOIUrl":null,"url":null,"abstract":"In this paper, a new method based on intuitionistic fuzzy sets is proposed to solve the partner selection problem in a manufacturing virtual enterprise. Based on the concept of average delivery time satisfaction degree, the formulated partner selection problem is interpreted so as to maximise the score of average delivery time satisfaction degree. The model takes into account the factors of average delivery time satisfaction degree, due date, cost and the precedence of tasks. To solve the problem, an improved particle swarm optimisation (PSO) algorithm is proposed. Finally, the simulation of a numerical example and comparisons with the standard PSO algorithm demonstrate that the improved PSO algorithm can effectively improve the searching quality, and the method is effective.","PeriodicalId":38792,"journal":{"name":"International Journal of Manufacturing Technology and Management","volume":"6 1","pages":"349-362"},"PeriodicalIF":0.0000,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Partner selection in a manufacturing virtual enterprise based on intuitionistic fuzzy sets\",\"authors\":\"Bin Huang, Liang Chen\",\"doi\":\"10.1504/IJMTM.2014.066694\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a new method based on intuitionistic fuzzy sets is proposed to solve the partner selection problem in a manufacturing virtual enterprise. Based on the concept of average delivery time satisfaction degree, the formulated partner selection problem is interpreted so as to maximise the score of average delivery time satisfaction degree. The model takes into account the factors of average delivery time satisfaction degree, due date, cost and the precedence of tasks. To solve the problem, an improved particle swarm optimisation (PSO) algorithm is proposed. Finally, the simulation of a numerical example and comparisons with the standard PSO algorithm demonstrate that the improved PSO algorithm can effectively improve the searching quality, and the method is effective.\",\"PeriodicalId\":38792,\"journal\":{\"name\":\"International Journal of Manufacturing Technology and Management\",\"volume\":\"6 1\",\"pages\":\"349-362\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Manufacturing Technology and Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJMTM.2014.066694\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Manufacturing Technology and Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJMTM.2014.066694","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
Partner selection in a manufacturing virtual enterprise based on intuitionistic fuzzy sets
In this paper, a new method based on intuitionistic fuzzy sets is proposed to solve the partner selection problem in a manufacturing virtual enterprise. Based on the concept of average delivery time satisfaction degree, the formulated partner selection problem is interpreted so as to maximise the score of average delivery time satisfaction degree. The model takes into account the factors of average delivery time satisfaction degree, due date, cost and the precedence of tasks. To solve the problem, an improved particle swarm optimisation (PSO) algorithm is proposed. Finally, the simulation of a numerical example and comparisons with the standard PSO algorithm demonstrate that the improved PSO algorithm can effectively improve the searching quality, and the method is effective.