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Variable weights theory and its application to multi-attribute group decision making with intuitionistic fuzzy numbers on determining decision maker’s weights

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  • Sen Liu
  • Wei Yu
  • Ling Liu
  • Yanan Hu

Abstract

The determination of the weights of decision makers (DMs) is an important problem in multi-attribute group decision making. Many approaches have been presented to determine DMs’ weights. However, the computed weight vectors of DMs are usually assumed to be constant in existing studies, and this may cause irrationalities in the decision results. Therefore, this article proposes a novel method to determine DMs’ weights based on variable weights theory in which the evaluation information is described as intuitionistic fuzzy sets (IFSs). First, DMs provide their assessment with IFSs, and the intuitionistic fuzzy weighted averaging (IFWA) operator is applied to obtain weighted decision matrix based on the prior given DMs’ and attributes’ weights. Second, the DMs’ weights are obtained based on variable weights theory, and an alternative decision can be computed. Finally, the converted value of the achieved IFS of each alternative is calculated, and the best appropriate alternative is acquired. Two illustrative examples and the comparisons with exsiting approaches are also used to reflect the effectiveness of the proposed approach.

Suggested Citation

  • Sen Liu & Wei Yu & Ling Liu & Yanan Hu, 2019. "Variable weights theory and its application to multi-attribute group decision making with intuitionistic fuzzy numbers on determining decision maker’s weights," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-21, March.
  • Handle: RePEc:plo:pone00:0212636
    DOI: 10.1371/journal.pone.0212636
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    References listed on IDEAS

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    1. Dong, Qingxing & Cooper, Orrin, 2016. "A peer-to-peer dynamic adaptive consensus reaching model for the group AHP decision making," European Journal of Operational Research, Elsevier, vol. 250(2), pages 521-530.
    2. Zeshui Xu, 2010. "A Deviation-Based Approach to Intuitionistic Fuzzy Multiple Attribute Group Decision Making," Group Decision and Negotiation, Springer, vol. 19(1), pages 57-76, January.
    3. Li, Yang & Wang, Jinlong & Zhao, Dongbo & Li, Guoqing & Chen, Chen, 2018. "A two-stage approach for combined heat and power economic emission dispatch: Combining multi-objective optimization with integrated decision making," Energy, Elsevier, vol. 162(C), pages 237-254.
    4. Eklund, Patrik & Rusinowska, Agnieszka & De Swart, Harrie, 2007. "Consensus reaching in committees," European Journal of Operational Research, Elsevier, vol. 178(1), pages 185-193, April.
    5. Qin, Jindong & Liu, Xinwang & Pedrycz, Witold, 2017. "An extended TODIM multi-criteria group decision making method for green supplier selection in interval type-2 fuzzy environment," European Journal of Operational Research, Elsevier, vol. 258(2), pages 626-638.
    6. Horace W. Brock, 1980. "The Problem of “Utility Weights” in Group Preference Aggregation," Operations Research, INFORMS, vol. 28(1), pages 176-187, February.
    7. Ramanathan, R. & Ganesh, L. S., 1994. "Group preference aggregation methods employed in AHP: An evaluation and an intrinsic process for deriving members' weightages," European Journal of Operational Research, Elsevier, vol. 79(2), pages 249-265, December.
    8. Samuel E. Bodily, 1979. "Note--A Delegation Process for Combining Individual Utility Functions," Management Science, INFORMS, vol. 25(10), pages 1035-1041, October.
    9. Wan, Shuping & Wang, Feng & Dong, Jiuying, 2017. "Additive consistent interval-valued Atanassov intuitionistic fuzzy preference relation and likelihood comparison algorithm based group decision making," European Journal of Operational Research, Elsevier, vol. 263(2), pages 571-582.
    10. Dariush Khezrimotlagh & Yao Chen, 2018. "The Optimization Approach," International Series in Operations Research & Management Science, in: Decision Making and Performance Evaluation Using Data Envelopment Analysis, chapter 0, pages 107-134, Springer.
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    Cited by:

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    2. Weidong Zhu & Shaorong Li & Hongtao Zhang & Tianjiao Zhang & Zhimin Li, 2022. "Evaluation of scientific research projects on the basis of evidential reasoning approach under the perspective of expert reliability," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 275-298, January.

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