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1.
PLoS One ; 16(5): e0251940, 2021.
Article in English | MEDLINE | ID: mdl-33984061

ABSTRACT

[This corrects the article DOI: 10.1371/journal.pone.0245187.].

2.
PLoS One ; 16(1): e0245187, 2021.
Article in English | MEDLINE | ID: mdl-33493184

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.


Subject(s)
Decision Making , Fuzzy Logic , Models, Theoretical , Uncertainty
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