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Consistency Improvement-Driven Decision-Making Methods with Probabilistic Multiplicative Preference Relations

Author

Listed:
  • Feifei Jin

    (Anhui University
    Texas A&M University)

  • Zhiwei Ni

    (Hefei University of Technology)

  • Reza Langari

    (Texas A&M University)

  • Huayou Chen

    (Anhui University)

Abstract

The hesitant multiplicative elements (HMEs) are useful tool to address situations in which the decision makers (DMs) are hesitant about several possible multiplicative values. However, the occurring probabilities of the elements in the HME are equal, which is obviously unpractical. To cope with this issue, this paper introduces the concept of probabilistic multiplicative preference relations (PMPRs), in which the occurring possibilities of the elements are considered in probabilistic multiplicative elements (PMEs). Then, several additional concepts are presented, including order consistent PMPRs and consistent PMPRs. A linear optimization model is established to generate the optimal deviation values, which is followed by an approach for constructing consistent PMPRs. For the unacceptable consistent PMPRs, two decision-making methods are further designed to improve their consistency until the adjusted PMPRs are acceptable, including automatic iterative decision-making algorithm and interactive decision-making algorithm. Finally, a numerical example of selecting the desirable supplier is provided, and the comparison with existing approaches is performed to validate the rationality and effectiveness of the proposed algorithms.

Suggested Citation

  • Feifei Jin & Zhiwei Ni & Reza Langari & Huayou Chen, 2020. "Consistency Improvement-Driven Decision-Making Methods with Probabilistic Multiplicative Preference Relations," Group Decision and Negotiation, Springer, vol. 29(2), pages 371-397, April.
    • Handle: RePEc:spr:grdene:v:29:y:2020:i:2:d:10.1007_s10726-020-09658-2
    DOI: 10.1007/s10726-020-09658-2
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    References listed on IDEAS

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    Cited by:

    1. Cong-Cong Li & Yuan Gao & Yucheng Dong, 2021. "Managing Ignorance Elements and Personalized Individual Semantics Under Incomplete Linguistic Distribution Context in Group Decision Making," Group Decision and Negotiation, Springer, vol. 30(1), pages 97-118, February.
    2. Cong-Cong Li & Yuan Gao & Yucheng Dong, 2023. "Managing Missing Preference Values Through Consistency and Consensus in Distributed Linguistic Preference Relations: A Two-stage Method Based on Personalized Individual Semantics," Group Decision and Negotiation, Springer, vol. 32(1), pages 125-146, February.
    3. Liu, Liyi & Tu, Yan & Zhang, Wen & Shen, Wenjing, 2024. "Supplier selection for emergency material based on group exponential TODIM method considering hesitant fuzzy linguistic set: A case study of China," Socio-Economic Planning Sciences, Elsevier, vol. 94(C).
    4. Feifei Jin & Jinpei Liu & Ligang Zhou & Luis Martínez, 2021. "Consensus-Based Linguistic Distribution Large-Scale Group Decision Making Using Statistical Inference and Regret Theory," Group Decision and Negotiation, Springer, vol. 30(4), pages 813-845, August.
    5. Wenqi Liu & Hengjie Zhang & Haiming Liang & Cong-cong Li & Yucheng Dong, 2022. "Managing Consistency and Consensus Issues in Group Decision-Making with Self-Confident Additive Preference Relations and Without Feedback: A Nonlinear Optimization Method," Group Decision and Negotiation, Springer, vol. 31(1), pages 213-240, February.

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