ArticleHeliyon2024
Power equipment supplier evaluation under a q-rung orthopair fuzzy set based decision making model.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The quality performance of power equipment suppliers is directly related to the stable and safe operation of the grid. This study presents a decision-making model based on q-rung orthopair fuzzy sets (q-ROFS) to evaluate suppliers, focusing on quality as the key criterion. To assess the objectivity and comprehensiveness of the results, we provide an innovative information fusion method that integrates the four dimensions of supply risk, supplier quality capability, profit impact, and willingness into the decision-making process. Considering the uncertainty and inconsistency in the decision-making process, in the weight determination stage, the q-ROFS-FWZIC method is used as the standard to allocate weights accurately. In the ranking stage, the q-ROFS-MABAC method was constructed to improve the consistency of evaluation results, and suppliers were ranked based on summarized performance data. A real-world case study involving power transformer suppliers illustrates the effectiveness of the proposed model. This research offers valuable insights for decision-makers in the power sector to optimize supplier selection, improve quality control measures, and ensure the ongoing reliability of the grid. Furthermore, this method can also be extended to other fields to solve various MCDM problems.
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