The coupled method fuzzy-AHP applys to solve multi-criteria decision making problems
Jiang Xin-pei, Zheng Bao, Liying Wang
Abstract
Jiang Xin-pei, Zheng Bao, Liying Wang
Abstract
The multi-criteria decision making (MCDM) problems with fuzzy preference information on alternatives are essential problems of the importance of weighting and ranking. In order to solve this problem, Analytical Hierarchy Process(AHP) and fuzzy comprehensive evaluation method are coupled to form a new approach named Fuzzy-AHP. This method is different from the traditional FAHP, which used to facilitate the pairwise comparison process and avoid the complex and unreliable process of comparing fuzzy utilities. It utilizes the advantage of AHP on computing index weight and comparing index in the same row than at ranking and the advantage of fuzzy comprehensive evaluation method on establishing quantitative indexes membership and qualitative indexes membership and classifying level. Finally, a numerical example is presented to clarify the methodology, the model evaluation results showed that the proposed system is able to provide very good solution both in accuracy, and speed for the top managers.
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The multi-criteria decision making (MCDM) problems with fuzzy preference information on alternatives are essential problems of the importance of weighting and ranking. In order to solve this problem, Analytical Hierarchy Process(AHP) and fuzzy comprehensive evaluation method are coupled to form a new approach named Fuzzy-AHP. This method is different from the traditional FAHP, which used to facilitate the pairwise comparison process and avoid the complex and unreliable process of comparing fuzzy utilities. It utilizes the advantage of AHP on computing index weight and comparing index in the same row than at ranking and the advantage of fuzzy comprehensive evaluation method on establishing quantitative indexes membership and qualitative indexes membership and classifying level. Finally, a numerical example is presented to clarify the methodology, the model evaluation results showed that the proposed system is able to provide very good solution both in accuracy, and speed for the top managers.
Key concepts: Analytic hierarchy process, Weighting, Ranking (information retrieval), Pairwise comparison, Multiple-criteria decision analysis, Data mining, Mathematics, Fuzzy logic