New computer methods for global optimization
New computer methods for global optimization
The Analytic Hierarchy Process--An Exposition
Operations Research
A common framework for deriving preference values from pairwise comparison matrices
Computers and Operations Research
Deriving weights from pairwise comparison matrices: The additive case
Operations Research Letters
A method for approximating pairwise comparison matrices by consistent matrices
Journal of Global Optimization
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Some multiple-criteria decision making methods rank actions by associating weights to the different criteria or actions, which are pairwise compared via a positive reciprocal matrix A. There is a vast literature on proposals of different mathematical-programming methods to infer weights from such matrix A. However, it is seldom observed that such optimization problems may be multimodal, thus the standard local-search resolution techniques suggested may be trapped in local optima, yielding a wrong ranking of alternatives. In this note we show that standard tools of global optimization based on interval analysis, lead to globally optimal weights in reasonable time.