{"title":"A fuzzy integral-based intuitionistic decision system for evaluation and improvement of suppliers in supply chain management","authors":"Li-Hui He, Guo-Fang Zhang, L. Song","doi":"10.1109/ICMLC.2014.7009709","DOIUrl":null,"url":null,"abstract":"In this paper, an intuitionistic fuzzy rule decision support system based on the fuzzy measure and the fuzzy integral is proposed to handle the various attributes associated with supplier evaluation problem in the supply chain management In this proposed decision support system, because of the importance of continuous evaluation of a particular supplier, the antecedent variable and the consequence variable in the fuzzy if-then rule are considered as the intuitionistic fuzzy variables based on the theory of intuitionistic fuzzy sets which is a generalized fuzzy set whose elements are characterized by both a membership and a non-membership to that set At the same time, given that decision with respect to the improvement and selection of suppliers is intrinsically multiple criteria decision making problem and is strategically important to enterprises, as well as the criteria are not actually independent where the interdependence of the criteria exists in supply chain network system. Evenly in the fact, there is the interdependence in the fuzzy if-then rules of the decision system in the actual supply chain case. Therefore the fuzzy measure and the fuzzy integral are applied to treat the above interdependence in presented system. Finally, the number experiment in a supply chain example shows that the reasoning process of the proposed decision support system provides a more reasonable representation of the real world.","PeriodicalId":335296,"journal":{"name":"2014 International Conference on Machine Learning and Cybernetics","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Machine Learning and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMLC.2014.7009709","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, an intuitionistic fuzzy rule decision support system based on the fuzzy measure and the fuzzy integral is proposed to handle the various attributes associated with supplier evaluation problem in the supply chain management In this proposed decision support system, because of the importance of continuous evaluation of a particular supplier, the antecedent variable and the consequence variable in the fuzzy if-then rule are considered as the intuitionistic fuzzy variables based on the theory of intuitionistic fuzzy sets which is a generalized fuzzy set whose elements are characterized by both a membership and a non-membership to that set At the same time, given that decision with respect to the improvement and selection of suppliers is intrinsically multiple criteria decision making problem and is strategically important to enterprises, as well as the criteria are not actually independent where the interdependence of the criteria exists in supply chain network system. Evenly in the fact, there is the interdependence in the fuzzy if-then rules of the decision system in the actual supply chain case. Therefore the fuzzy measure and the fuzzy integral are applied to treat the above interdependence in presented system. Finally, the number experiment in a supply chain example shows that the reasoning process of the proposed decision support system provides a more reasonable representation of the real world.