{"title":"Ranking of Alternatives in Multiple Attribute Group Decision Making: A Fuzzy Preference Relation Based Approach","authors":"Sujit Das, P. Ghosh, S. Kar","doi":"10.1109/ISCBI.2013.34","DOIUrl":null,"url":null,"abstract":"This paper presents a two phase approach for fuzzy multiple attributes group decision making based on fuzzy preference relations (FPR). In the first phase, incomplete fuzzy preference relations provided by the decision makers are completed based on the procedure proposed by Herrera-Viedma et al. (2007). Second phase focuses the selection of best alternative(s) among a set of alternatives based on average rating value and score of alternatives with respect to decision makers. Initially the average rating value of each decision maker with respect to the alternatives are calculated and sorted in descending order. Based on their sorting, suitable score values are assigned to them and then calculate the summation values of the scores of the alternatives with respect to each decision maker. When summations of scores are same, summation of average rating value for each expert on individual alternatives is calculated to rank those alternatives. Larger summation values of the scores gives better choice to the alternative. Finally, this approach is analyzed with a numerical example and the result is compared with the experiment executed by Herrera-Viedma et al. (2007).","PeriodicalId":311471,"journal":{"name":"2013 International Symposium on Computational and Business Intelligence","volume":"85 3","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Symposium on Computational and Business Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCBI.2013.34","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This paper presents a two phase approach for fuzzy multiple attributes group decision making based on fuzzy preference relations (FPR). In the first phase, incomplete fuzzy preference relations provided by the decision makers are completed based on the procedure proposed by Herrera-Viedma et al. (2007). Second phase focuses the selection of best alternative(s) among a set of alternatives based on average rating value and score of alternatives with respect to decision makers. Initially the average rating value of each decision maker with respect to the alternatives are calculated and sorted in descending order. Based on their sorting, suitable score values are assigned to them and then calculate the summation values of the scores of the alternatives with respect to each decision maker. When summations of scores are same, summation of average rating value for each expert on individual alternatives is calculated to rank those alternatives. Larger summation values of the scores gives better choice to the alternative. Finally, this approach is analyzed with a numerical example and the result is compared with the experiment executed by Herrera-Viedma et al. (2007).
提出了一种基于模糊偏好关系的模糊多属性群体决策的两阶段方法。在第一阶段,根据Herrera-Viedma et al.(2007)提出的程序完成决策者提供的不完全模糊偏好关系。第二阶段的重点是根据决策者对备选方案的平均评价值和得分,从一组备选方案中选出最佳备选方案。首先计算每个决策者相对于备选方案的平均评级值,并按降序排序。在对其排序的基础上,为其分配合适的得分值,然后计算各备选方案相对于每个决策者的得分之和。当得分的总和相同时,计算每个专家对单个备选方案的平均评分值的总和,对这些备选方案进行排名。分数的总和越大,对备选项的选择就越好。最后,通过一个数值算例对该方法进行了分析,并将结果与Herrera-Viedma et al.(2007)的实验结果进行了比较。