Membership maximization prioritization methods for fuzzy analytic hierarchy process

Fuzzy analytic hierarchy process (FAHP) has increasingly been applied in many areas. Extent analysis method is the popular tool for prioritization in FAHP, although significant technical errors are identified in this study. With addressing the errors, this research proposes membership maximization prioritization methods (MMPMs) using different membership functions as the novel solutions. As a lack of research about effectiveness measurement on the crisp/fuzzy prioritization methods, this study proposes membership fitness index to evaluate the effectiveness of the prioritization methods. Comparisons with the other popular fuzzy/crisp prioritization methods including modified fuzzy preference programming, Direct least squares, and Eigen value are conducted and analyses indicate that MMPMs lead to much more reliable result in view of membership fitness index. A numerical example demonstrates the usability of MMPMs for FAHP, and thus MMPMs can effectively be applied to various decision analysis applications.