{"title":"基于WGA算子和灰色关联分析的多属性群决策方法","authors":"Qiuping Wang, Subing Liu, Guoqiang Xiong","doi":"10.1108/GS-02-2015-0004","DOIUrl":null,"url":null,"abstract":"A method for multiple attribute group decision making via the WGA operator and Grey Incidence Analysis is given, in which the weighted geometric aggregation (WGA) operator provides aggregation of attribute values of an alternative to form an overall decision for each decision expert, the group aggregation model is established based on the maximization the sum of grey incidence degree between each decision expert and ideal expert. The distinguishing feature of the WGA operator is that, when an attribute value among attribute values of an alternative is on the low side, it will have a significant impact on the overall evaluation of the alternative. The proposed method is suitable for group decision making problems in which the attribute weights are known, but the expert weights are completely unknown.","PeriodicalId":246110,"journal":{"name":"2015 IEEE International Conference on Grey Systems and Intelligent Services (GSIS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Multiple attribute group decision making method based on WGA operator and Grey Incidence Analysis\",\"authors\":\"Qiuping Wang, Subing Liu, Guoqiang Xiong\",\"doi\":\"10.1108/GS-02-2015-0004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A method for multiple attribute group decision making via the WGA operator and Grey Incidence Analysis is given, in which the weighted geometric aggregation (WGA) operator provides aggregation of attribute values of an alternative to form an overall decision for each decision expert, the group aggregation model is established based on the maximization the sum of grey incidence degree between each decision expert and ideal expert. The distinguishing feature of the WGA operator is that, when an attribute value among attribute values of an alternative is on the low side, it will have a significant impact on the overall evaluation of the alternative. The proposed method is suitable for group decision making problems in which the attribute weights are known, but the expert weights are completely unknown.\",\"PeriodicalId\":246110,\"journal\":{\"name\":\"2015 IEEE International Conference on Grey Systems and Intelligent Services (GSIS)\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE International Conference on Grey Systems and Intelligent Services (GSIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/GS-02-2015-0004\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Grey Systems and Intelligent Services (GSIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/GS-02-2015-0004","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multiple attribute group decision making method based on WGA operator and Grey Incidence Analysis
A method for multiple attribute group decision making via the WGA operator and Grey Incidence Analysis is given, in which the weighted geometric aggregation (WGA) operator provides aggregation of attribute values of an alternative to form an overall decision for each decision expert, the group aggregation model is established based on the maximization the sum of grey incidence degree between each decision expert and ideal expert. The distinguishing feature of the WGA operator is that, when an attribute value among attribute values of an alternative is on the low side, it will have a significant impact on the overall evaluation of the alternative. The proposed method is suitable for group decision making problems in which the attribute weights are known, but the expert weights are completely unknown.