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Fuzzy Group Decision Making for Multiobjective Problems: Tradeoff between Consensus and Robustness

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  • Jian Xiong
  • Xu Tan
  • Ke-wei Yang
  • Ying-wu Chen

Abstract

Many decision making problems involve multiple decision makers and conflicting objectives. This paper refers to this kind of problems as group decision making for multiobjective problems (GDM-MOP). The task of GDM-MOP is to select final solution(s) from a set of nondominated solutions according to the decision makers' preferences. However, it is common that the preference could be imprecise. We study the GDM-MOP where preferences are expressed by fuzzy reference points, called as fuzzy GDMMOP (FGDM-MOP). This paper provides a decision support model to simultaneously consider two measures for FGDM-MOP: consensus measure and robustness measure. The former is used to reflect the acceptable degree of a solution by the decision making group, while the latter indicates a solution's ability to cope with any change on preferences. A multiobjective evolutionary approach is presented to solve the problem. Finally, a modified benchmark function is studied to illustrate the proposed approach.

Suggested Citation

  • Jian Xiong & Xu Tan & Ke-wei Yang & Ying-wu Chen, 2013. "Fuzzy Group Decision Making for Multiobjective Problems: Tradeoff between Consensus and Robustness," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-9, August.
  • Handle: RePEc:hin:jnljam:657978
    DOI: 10.1155/2013/657978
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    Cited by:

    1. Eduardo Fernández & Claudia Gómez-Santillán & Nelson Rangel-Valdez & Laura Cruz-Reyes, 2022. "Group Multi-Objective Optimization Under Imprecision and Uncertainty Using a Novel Interval Outranking Approach," Group Decision and Negotiation, Springer, vol. 31(5), pages 945-994, October.
    2. Balderas, Fausto & Fernández, Eduardo & Cruz-Reyes, Laura & Gómez-Santillán, Claudia & Rangel-Valdez, Nelson, 2022. "Solving group multi-objective optimization problems by optimizing consensus through multi-criteria ordinal classification," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1014-1029.

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