Comparative Sensitivity Analysis of Some Fuzzy AHP Methods

Abstract

A precise evaluation of the actual situation is a significant aspect of making a correct and informed decision. Due to the bounded accuracy and elements of uncertainty in the data itself, a point estimate may be less adjusted and rough than an estimate based on fuzzy set theory. The stability of the Fuzzy AHP Arithmetic mean, Geometric mean, Extent analysis, and Lambda Max methods, widely used in practice, is verified. Three stages of verification are considered, investigating the impact of the following: (a) the scale applied; (b) methods of aggregation of the AHP matrices into the FAHP matrix; and (c) methods of combining several FAHP judgments. Slight changes in experts’ estimates are programmatically simulated tens of thousands of times to track changes in ranking and deviations of results from the initial estimate. This continues the study of FAHP’s stability due to the ambiguous results of such verification by the method of extent analysis. As a result of a comparative analysis of the listed evaluation methods, their specific features and advantages are identified.

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