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Mathematics 2019, 7(2), 179; https://doi.org/10.3390/math7020179

A Partial-Consensus Posterior-Aggregation FAHP Method—Supplier Selection Problem as an Example

1
Department of Industrial Engineering and Management, Chaoyang University of Technology, Taichung 41349, Taiwan
2
Department of Industrial Engineering and Management, National Chiao Tung University, 1001, University Road, Hsinchu 300, Taiwan
*
Author to whom correspondence should be addressed.
Received: 18 January 2019 / Revised: 8 February 2019 / Accepted: 11 February 2019 / Published: 15 February 2019
(This article belongs to the Special Issue Fuzzy Sets, Fuzzy Logic and Their Applications)
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Abstract

Existing fuzzy analytic hierarchy process (FAHP) methods usually aggregate the fuzzy pairwise comparison results produced by multiple decision-makers (DMs) rather than the fuzzy weights estimations. This is problematic because fuzzy pairwise comparison results are subject to uncertainty and lack consensus. To address this problem, a partial-consensus posterior-aggregation FAHP (PCPA-FAHP) approach is proposed in this study. The PCPA-FAHP approach seeks a partial consensus among most DMs instead of an overall consensus among all DMs, thereby increasing the possibility of reaching a consensus. Subsequently, the aggregation result is defuzzified using the prevalent center-of-gravity method. The PCPA-FAHP approach was applied to a supplier selection problem to validate its effectiveness. According to the experimental results, the PCPA-FAHP approach not only successfully found out the partial consensus among the DMs, but also shrunk the widths of the estimated fuzzy weights to enhance the precision of the FAHP analysis. View Full-Text
Keywords: fuzzy analytic hierarchy process; decision-making; partial consensus; posterior aggregation fuzzy analytic hierarchy process; decision-making; partial consensus; posterior aggregation
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Wang, Y.-C.; Chen, T.-C.T. A Partial-Consensus Posterior-Aggregation FAHP Method—Supplier Selection Problem as an Example. Mathematics 2019, 7, 179.

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