{"title":"可靠性最大化的多目标模糊随机工程优化","authors":"C. Shih, C.S. Wang","doi":"10.1109/AFSS.1996.583618","DOIUrl":null,"url":null,"abstract":"This paper introduces a design methodology using fuzzy theory to find random design variables by maximizing the reliability as well as optimizing multiobjectives. The formulation of the problem involves random parameters and probabilistic and fuzzy probabilistic constraints. The objective weighting strategy in the multiobjective fuzzy formulation is presented. An engineering design example illustrates this optimization process and the solution techniques.","PeriodicalId":197019,"journal":{"name":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multiobjective fuzzy and stochastic engineering optimization with maximizing reliability\",\"authors\":\"C. Shih, C.S. Wang\",\"doi\":\"10.1109/AFSS.1996.583618\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces a design methodology using fuzzy theory to find random design variables by maximizing the reliability as well as optimizing multiobjectives. The formulation of the problem involves random parameters and probabilistic and fuzzy probabilistic constraints. The objective weighting strategy in the multiobjective fuzzy formulation is presented. An engineering design example illustrates this optimization process and the solution techniques.\",\"PeriodicalId\":197019,\"journal\":{\"name\":\"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-12-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AFSS.1996.583618\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AFSS.1996.583618","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multiobjective fuzzy and stochastic engineering optimization with maximizing reliability
This paper introduces a design methodology using fuzzy theory to find random design variables by maximizing the reliability as well as optimizing multiobjectives. The formulation of the problem involves random parameters and probabilistic and fuzzy probabilistic constraints. The objective weighting strategy in the multiobjective fuzzy formulation is presented. An engineering design example illustrates this optimization process and the solution techniques.