Fuzzy algorithm for group decision making with participants having finite discriminating abilities

Authors:
Carlos Kobashikawa;Yutaka Hatakeyama;Fangyan Dong;Kaoru Hirota
Affiliations:
Department of Computational Intelligence and Systems Science, Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, Yokohama, Japan;Center of Medical Information Science, Medical School, Kochi University, Kochi, Japan;Department of Computational Intelligence and Systems Science, Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, Yokohama, Japan;Department of Computational Intelligence and Systems Science, Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, Yokohama, Japan
Venue:
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special section: Best papers from the 2007 biometrics: Theory, applications, and systems (BTAS 07) conference
Year:
2009

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Abstract

A fuzzy inference-based algorithm with rules using the Nash solution is proposed for group decision making considering the finite discriminating abilities of real decision makers (DMs). It provides a solution that can capture and incorporate the imprecision of real people at declaring their preferences, and hence, it reflects more faithfully the DMs' opinions. The algorithm is applied to a purchase project of a storage area network with two DMs and three options. It shows how the algorithm can provide a unique solution whereas customary crisp methods are either unable to do it or reveal a risk of choosing, in 16.5% of the cases, an option that does not match with the preferences declared by the group of DMs as a whole. The algorithm aims for processes where the options are difficult to evaluate, circumstance that makes clear that human beings cannot provide unreal crisp values, and that the solution changes if preference information is only partially taken.