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A Consensus Model For Group Decision-Making Problems With Interval Fuzzy Preference Relations

Author

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  • J. M. TAPIA GARCÍA

    (Dept. of Cuantitative Methods in Economy and Enterprise, University of Granada, 18071 Granada, Spain)

  • M. J. DEL MORAL

    (Dept. of Statistics and Operational Research, University of Granada, 18071 Granada, Spain)

  • M. A. MARTÍNEZ

    (Dept. of Computer Science and A.I, University of Granada, 18071 Granada, Spain)

  • E. HERRERA-VIEDMA

    (Dept. of Computer Science and A.I, University of Granada, 18071 Granada, Spain)

Abstract

Interval fuzzy preference relations can be useful to express decision makers' preferences in group decision-making problems. Usually, we apply a selection process and a consensus process to solve a group decision situation. In this paper, we present a consensus model for group decision-making problems with interval fuzzy preference relations. This model is based on two consensus criteria, a consensus measure and a proximity measure, and also on the concept of coincidence among preferences. We compute both consensus criteria in the three representation levels of a preference relation and design an automatic feedback mechanism to guide experts in the consensus reaching process. We show an application example in social work.

Suggested Citation

  • J. M. Tapia García & M. J. Del Moral & M. A. Martínez & E. Herrera-Viedma, 2012. "A Consensus Model For Group Decision-Making Problems With Interval Fuzzy Preference Relations," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 11(04), pages 709-725.
    • Handle: RePEc:wsi:ijitdm:v:11:y:2012:i:04:n:s0219622012500174
    DOI: 10.1142/S0219622012500174
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    Cited by:

    1. Karasan, Ali & Erdogan, Melike & Cinar, Melih, 2022. "Healthcare service quality evaluation: An integrated decision-making methodology and a case study," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).
    2. Juan Carlos Leyva-López, 2024. "A consistency and consensus model for group decision support based on the outranking approach," Operational Research, Springer, vol. 24(2), pages 1-29, June.
    3. Goran Petrović & Jelena Mihajlović & Danijel Marković & Sarfaraz Hashemkhani Zolfani & Miloš Madić, 2023. "Comparison of Aggregation Operators in the Group Decision-Making Process: A Real Case Study of Location Selection Problem," Sustainability, MDPI, vol. 15(10), pages 1-22, May.
    4. Jing Yan & Xinping Guan & Xiaoyuan Luo & Cailian Chen, 2017. "Formation Control and Obstacle Avoidance for Multi-Agent Systems Based on Virtual Leader-Follower Strategy," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(03), pages 865-880, May.
    5. Deng-Feng Li & Shu-Ping Wan, 2017. "Minimum Weighted Minkowski Distance Power Models for Intuitionistic Fuzzy Madm with Incomplete Weight Information," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(05), pages 1387-1408, September.
    6. Jie Tang & Fanyong Meng & Francisco Javier Cabrerizo & Enrique Herrera-Viedma, 2019. "A procedure for group decision making with interval-valued intuitionistic linguistic fuzzy preference relations," Fuzzy Optimization and Decision Making, Springer, vol. 18(4), pages 493-527, December.
    7. Zhang, Huanhuan & Kou, Gang & Peng, Yi, 2019. "Soft consensus cost models for group decision making and economic interpretations," European Journal of Operational Research, Elsevier, vol. 277(3), pages 964-980.

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