{"title":"模糊随机环境下多项目供应商选择问题的分散双层优化","authors":"Yan Tu, Xiaoyang Zhou, B. Lev","doi":"10.1109/CSO.2014.137","DOIUrl":null,"url":null,"abstract":"The aim of this paper is to consider the supplier selection problem under a hierarchical decision system. With consideration of the inherent uncertainty, An decentralized bilevel optimization model under fuzzy random environment is developed for tracking a supplier selection problem with multiple items. For solving the bi-level programming model, an interactive fuzzy programming technique and an improved particle swarm optimization based on fuzzy random simulation (IPSO based FRS) are designed as a combined solution method. Finally, the results and comparisons analysis of a case study are presented to demonstrate the practicality and efficiency of the optimization method.","PeriodicalId":174800,"journal":{"name":"2014 Seventh International Joint Conference on Computational Sciences and Optimization","volume":"278 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Decentralized Bilevel Optimization for Supplier Selection Problem with Multiple Items under Fuzzy Random Environment\",\"authors\":\"Yan Tu, Xiaoyang Zhou, B. Lev\",\"doi\":\"10.1109/CSO.2014.137\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The aim of this paper is to consider the supplier selection problem under a hierarchical decision system. With consideration of the inherent uncertainty, An decentralized bilevel optimization model under fuzzy random environment is developed for tracking a supplier selection problem with multiple items. For solving the bi-level programming model, an interactive fuzzy programming technique and an improved particle swarm optimization based on fuzzy random simulation (IPSO based FRS) are designed as a combined solution method. Finally, the results and comparisons analysis of a case study are presented to demonstrate the practicality and efficiency of the optimization method.\",\"PeriodicalId\":174800,\"journal\":{\"name\":\"2014 Seventh International Joint Conference on Computational Sciences and Optimization\",\"volume\":\"278 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-07-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 Seventh International Joint Conference on Computational Sciences and Optimization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSO.2014.137\",\"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 Seventh International Joint Conference on Computational Sciences and Optimization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSO.2014.137","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
研究了层次决策系统下的供应商选择问题。针对多项目供应商选择问题,考虑其固有的不确定性,建立了模糊随机环境下的分散双层优化模型。为了求解双层规划模型,设计了一种交互式模糊规划技术和基于模糊随机模拟的改进粒子群优化(IPSO based FRS)相结合的求解方法。最后,通过实例分析和对比分析,验证了该优化方法的实用性和有效性。
Decentralized Bilevel Optimization for Supplier Selection Problem with Multiple Items under Fuzzy Random Environment
The aim of this paper is to consider the supplier selection problem under a hierarchical decision system. With consideration of the inherent uncertainty, An decentralized bilevel optimization model under fuzzy random environment is developed for tracking a supplier selection problem with multiple items. For solving the bi-level programming model, an interactive fuzzy programming technique and an improved particle swarm optimization based on fuzzy random simulation (IPSO based FRS) are designed as a combined solution method. Finally, the results and comparisons analysis of a case study are presented to demonstrate the practicality and efficiency of the optimization method.