{"title":"模糊机会约束的投资组合选择","authors":"Li-mei Yan","doi":"10.1109/JCAI.2009.133","DOIUrl":null,"url":null,"abstract":"The aim of this paper is to solve the portfolio problem when security returns are bifuzzy variables. Two types of portfolio selections based on chance measure are provided according to bifuzzy theory. Since the proposed optimization problems are difficult to solve by traditional methods, A hybrid intelligent algorithm by integrating bifuzzy simulation and genetic algorithm is designed. Finally, one numerical experiment is provided to illustrate the effectiveness of the algorithm.","PeriodicalId":154425,"journal":{"name":"2009 International Joint Conference on Artificial Intelligence","volume":"70 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Bifuzzy Chance-constrained Portfolio Selection\",\"authors\":\"Li-mei Yan\",\"doi\":\"10.1109/JCAI.2009.133\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The aim of this paper is to solve the portfolio problem when security returns are bifuzzy variables. Two types of portfolio selections based on chance measure are provided according to bifuzzy theory. Since the proposed optimization problems are difficult to solve by traditional methods, A hybrid intelligent algorithm by integrating bifuzzy simulation and genetic algorithm is designed. Finally, one numerical experiment is provided to illustrate the effectiveness of the algorithm.\",\"PeriodicalId\":154425,\"journal\":{\"name\":\"2009 International Joint Conference on Artificial Intelligence\",\"volume\":\"70 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-04-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Joint Conference on Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/JCAI.2009.133\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Joint Conference on Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/JCAI.2009.133","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The aim of this paper is to solve the portfolio problem when security returns are bifuzzy variables. Two types of portfolio selections based on chance measure are provided according to bifuzzy theory. Since the proposed optimization problems are difficult to solve by traditional methods, A hybrid intelligent algorithm by integrating bifuzzy simulation and genetic algorithm is designed. Finally, one numerical experiment is provided to illustrate the effectiveness of the algorithm.
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