TOP 活動実績 2010年

(15) A Fuzzy Weights Representation for Inner Dependence AHP using Sensitivity Analysis

Shin-ichi Ohnishi, Takahiro Yamanoi, Hideyuki Imai
The 7th International Conference on Modeling Decisions for Artificial Intelligence(MDAI2010),2010-10

The inner dependence method AHP (Analytic Hierarchy Process) is one technique of decision making for the case in which criteria do not have enough independency. However using original AHP or inner dependence method, the data and results often lose their reliability because the comparison matrix does not always have sufficient consistency. In these cases, fuzzy representation for weighting criteria and alternatives using results from a sensitivity analysis is useful. In this paper, we first present weights of criteria of normal AHP by means of fuzzy sets, then modified fuzzy weights is calculated. Overall weights of alternatives can also be calculated by employing some assumptions. It can show how the results of the inner dependence AHP contain fuzziness when the comparison matrix is not sufficiently consistent and each criterion has not enough independency.

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