{"title":"Fuzzy decision making through relationships analysis between criteria","authors":"J. Lee, J. Kuo, W.T. Huang","doi":"10.1109/AFSS.1996.583617","DOIUrl":null,"url":null,"abstract":"A criteria trade-off analysis approach, based on relationships analysis for fuzzy decision-making, is proposed. The degrees of conflict and cooperation between any two individual criteria are first formulated. Relationships between individual criteria are identified based upon their conflicting and cooperative degrees. The criteria are converted into a disjunctive normal form to obtain a uniform representation of the criteria, and then arranged into a four-level hierarchical aggregation structure. A set of parameterized aggregation (fuzzy AND/OR) operators is selected to aggregate the judgements for the alternatives. A compromise alternative, which is proven to satisfy Pareto optimality, can thus be obtained based on the aggregation hierarchical structure.","PeriodicalId":197019,"journal":{"name":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","volume":"104 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","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.1996.583617","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
A criteria trade-off analysis approach, based on relationships analysis for fuzzy decision-making, is proposed. The degrees of conflict and cooperation between any two individual criteria are first formulated. Relationships between individual criteria are identified based upon their conflicting and cooperative degrees. The criteria are converted into a disjunctive normal form to obtain a uniform representation of the criteria, and then arranged into a four-level hierarchical aggregation structure. A set of parameterized aggregation (fuzzy AND/OR) operators is selected to aggregate the judgements for the alternatives. A compromise alternative, which is proven to satisfy Pareto optimality, can thus be obtained based on the aggregation hierarchical structure.
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