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A Hybrid Fuzzy Approach To Fuzzy Multi-Attribute Group Decision-Making

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  • ZHI-XIN SU

    (School of Economics and Management, Beihang University, No. 37 Xueyuan Road, Haidian District, Beijing 100191, P. R. China)

Abstract

The paper investigates fuzzy multi-attribute group decision-making (FMAGDM) problems. The important weights of the attributes and the ratings of the alternatives with respect to each attribute provided by multiple decision-makers are described by the linguistic variables expressed in triangular fuzzy numbers or trapezoidal fuzzy numbers. A hybrid fuzzy approach is proposed, which assesses each alternative in terms of distance measure calculated by a modified VIKOR method as well as similarity measure calculated by a modified gray relational analysis (GRA) method, to the positive ideal alternative and the negative ideal alternative. A new relative closeness coefficient is established to rank alternatives by aggregating the distance and the similarity measures. Two numerical examples for reverse logistics applications are presented to illustrate the proposed method.

Suggested Citation

  • Zhi-Xin Su, 2011. "A Hybrid Fuzzy Approach To Fuzzy Multi-Attribute Group Decision-Making," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 10(04), pages 695-711.
  • Handle: RePEc:wsi:ijitdm:v:10:y:2011:i:04:n:s021962201100452x
    DOI: 10.1142/S021962201100452X
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    Citations

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    Cited by:

    1. Juan-Juan Peng & Jian-Qiang Wang & Xiao-Hui Wu, 2016. "Novel Multi-criteria Decision-making Approaches Based on Hesitant Fuzzy Sets and Prospect Theory," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(03), pages 621-643, May.
    2. Michael C. Nwogugu, 2020. "Decision-Making, Sub-Additive Recursive "Matching" Noise And Biases In Risk-Weighted Stock/Bond Index Calculation Methods In Incomplete Markets With Partially Observable Multi-Attribute Pref," Papers 2005.01708, arXiv.org.
    3. Yiming Tang & Fuji Ren, 2017. "Fuzzy Systems Based on Universal Triple I Method and Their Response Functions," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(02), pages 443-471, March.
    4. Chun-Hao Chen & Tzung-Pei Hong & Yeong-Chyi Lee & Vincent S. Tseng, 2015. "Finding Active Membership Functions for Genetic-Fuzzy Data Mining," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 14(06), pages 1215-1242, November.
    5. Paulo Cesar Schotten & Danielle Costa Morais, 2019. "A group decision model for credit granting in the financial market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-19, December.
    6. Fahim ul Amin & Qian-Li Dong & Katarzyna Grzybowska & Zahid Ahmed & Bo-Rui Yan, 2022. "A Novel Fuzzy-Based VIKOR–CRITIC Soft Computing Method for Evaluation of Sustainable Supply Chain Risk Management," Sustainability, MDPI, vol. 14(5), pages 1-15, February.
    7. Mehdi KESHAVARZ GHORABAEE & Edmundas Kazimieras ZAVADSKAS & Maghsoud AMIRI & Jurgita ANTUCHEVICIENE, 2016. "A New Method Of Assessment Based On Fuzzy Ranking And Aggregated Weights (Afraw) For Mcdm Problems Under Type-2 Fuzzy Environment," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(1), pages 39-68.

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