Comparing Two Approaches for Consensus Computation in Group Decision Making Problems

Abstract

In group decision making problems, the soft consensus calculus is an important topic. Soft consensus measures are utilized to show the different agreement degrees between decisors. Using the concept of coincidence we have two main approaches to calculating soft consensus measures: concordance among expert preferences and concordance among individual solutions. In the first, the coincidence is obtained by evaluating the similarity among the expert preferences, while in the second one the concordance is derived from the measurement of the similarity among the solutions proposed by these decisors or experts. In this paper we perform a basic comparative study of consensus calculus based on both coincidence approaches. We use the nonparametric Wilcoxon signed-ranks test to compare these approaches. We obtain significant differences between both approaches for measuring consensus.

Description

Keywords

Group decision making, fuzzy preference relations, consensus, Wilcoxon test

Citation

Del Moral, M.J., Tapia Garcia, J.M., Chiclana, F., Herrera-Viedma, E. (2018) Comparing Two Approaches for Consensus Computation in Group Decision Making Problems. In: Fujita, H., Herrera-Viedma, E. (Eds.) New Trends in Intelligent Software Methodologies, Tools and Techniques. Frontiers in Artificial Intelligence and Applications, 303, pp.312 - 320.

Rights

Research Institute

Institute of Artificial Intelligence (IAI)