{"title":"Particle swam optimization based reliability-redundancy allocation in a type-2 fuzzy environment","authors":"Zubair Ashraf, Pranab K. Muhuri, Q. Lohani","doi":"10.1109/CEC.2015.7257027","DOIUrl":null,"url":null,"abstract":"In this paper, we have addressed the reliability-redundancy allocation problem with a particle swam optimization based technique. The parameters of the system components are actually imprecise or uncertain quantity since those are generally guessed by the designers during the design-time. Thus, important features of the designed system, viz. reliability, costs, weight etc very suitably qualifies to be considered as fuzzy quantity. Our problem formulation considers these parameters as type-2 fuzzy quantity. There are few reports where the problem has been studied under type-1 fuzzy uncertainty. As far as we know, no research has been reported where the problem has been addressed with a particle swam optimization based approach in a type-2 fuzzy environment. Suitable examples are included to demonstrate our approach. Results are compared showing that the type-2 fuzzy uncertainty based approach outperforms other recently reported results.","PeriodicalId":403666,"journal":{"name":"2015 IEEE Congress on Evolutionary Computation (CEC)","volume":"351 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Congress on Evolutionary Computation (CEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CEC.2015.7257027","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 23
Abstract
In this paper, we have addressed the reliability-redundancy allocation problem with a particle swam optimization based technique. The parameters of the system components are actually imprecise or uncertain quantity since those are generally guessed by the designers during the design-time. Thus, important features of the designed system, viz. reliability, costs, weight etc very suitably qualifies to be considered as fuzzy quantity. Our problem formulation considers these parameters as type-2 fuzzy quantity. There are few reports where the problem has been studied under type-1 fuzzy uncertainty. As far as we know, no research has been reported where the problem has been addressed with a particle swam optimization based approach in a type-2 fuzzy environment. Suitable examples are included to demonstrate our approach. Results are compared showing that the type-2 fuzzy uncertainty based approach outperforms other recently reported results.