2014/08/26 by Sujit Das, Das, Sujit, Samarjit Kar +1
Computer Science · Decision Sciences · #Artificial Intelligence (cs.AI) #Data Management and Algorithms #FOS: Computer and information sciences #Fuzzy and Soft Set Theory #Multi-Criteria Decision Making
paper · pdf · doi:10.48550/arxiv.1408.6186
openalex publication_date 2014/08/26 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28
In group decision making (GDM) problems fuzzy preference relations (FPR) are widely used for representing decision makers' opinions on the set of alternatives. In order to avoid misleading solutions, the study of consistency and consensus has become a very important aspect. This article presents a simulated annealing (SA) based soft computing approach to optimize the consistency/consensus level (CCL) of a complete fuzzy preference relation in order to solve a GDM problem. Consistency level indicates as expert's preference quality and consensus level measures the degree of agreement among experts' opinions. This study also suggests the set of experts for the necessary modifications in their prescribed preference structures without intervention of any moderator.