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A dynamic generalized fuzzy multi-criteria croup decision making approach for green supplier segmentation

Author

Listed:
  • Do Anh Duc
  • Luu Huu Van
  • Vincent F Yu
  • Shuo-Yan Chou
  • Ngo Van Hien
  • Ngo The Chi
  • Dinh Van Toan
  • Luu Quoc Dat

Abstract

Supplier selection and segmentation are crucial tasks of companies in order to reduce costs and increase the competitiveness of their goods. To handle uncertainty and dynamicity in the supplier segmentation problem, this research thus proposes a new dynamic generalized fuzzy multi-criteria group decision making (MCGDM) approach from the aspects of capability and willingness and with respect to environmental issues. The proposed approach defines the aggregated ratings of alternatives, the aggregated weights of criteria, and the weighted ratings by using generalized fuzzy numbers with the effect of time weight. Next, we determine the ranking order of alternatives via a popular centroid-index ranking approach. Finally, two case studies demonstrate the efficiency of the proposed dynamic approach. The applications show that the proposed appoach is effective in solving the MCGDM in vague environment.

Suggested Citation

  • Do Anh Duc & Luu Huu Van & Vincent F Yu & Shuo-Yan Chou & Ngo Van Hien & Ngo The Chi & Dinh Van Toan & Luu Quoc Dat, 2021. "A dynamic generalized fuzzy multi-criteria croup decision making approach for green supplier segmentation," PLOS ONE, Public Library of Science, vol. 16(1), pages 1-13, January.
    • Handle: RePEc:plo:pone00:0245187
    DOI: 10.1371/journal.pone.0245187
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    References listed on IDEAS

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    1. Hosseini, Seyedmohsen & Morshedlou, Nazanin & Ivanov, Dmitry & Sarder, M.D. & Barker, Kash & Khaled, Abdullah Al, 2019. "Resilient supplier selection and optimal order allocation under disruption risks," International Journal of Production Economics, Elsevier, vol. 213(C), pages 124-137.
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    Cited by:

    1. Fakhradin Ghasemi & Mohammad Babamiri & Zahra Pashootan, 2022. "A comprehensive method for the quantification of medication error probability based on fuzzy SLIM," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-17, February.
    2. Thalles Vitelli Garcez & Helder Tenório Cavalcanti & Adiel Teixeira de Almeida, 2021. "A hybrid decision support model using Grey Relational Analysis and the Additive-Veto Model for solving multicriteria decision-making problems: an approach to supplier selection," Annals of Operations Research, Springer, vol. 304(1), pages 199-231, September.

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