Approaches to consistency adjustment
Journal of Optimization Theory and Applications
On the order of the preference intensities in fuzzy AHP
Computers and Industrial Engineering
Computers and Operations Research
Robust decision making using data envelopment analytic hierarchy process
AIKED'08 Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases
Expert Systems with Applications: An International Journal
Recent Literature Collected by Didier DUBOIS, Henri PRADE and Salvatore SESSA
Fuzzy Sets and Systems
Prioritizing alternative using evolutionary computing procedure in AHP
AIKED'10 Proceedings of the 9th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases
Deriving priority in AHP using evolutionary computing approach
WSEAS Transactions on Information Science and Applications
A two-phase algorithm for product part change utilizing AHP and PSO
Expert Systems with Applications: An International Journal
Enumerating all spanning trees for pairwise comparisons
Computers and Operations Research
A linguistic evaluation approach for universal design
Information Sciences: an International Journal
Building Socially-Aware E-Learning Systems Through Knowledge Management
International Journal of Knowledge Management
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A multicriteria approach for combining prioritization methods within the analytic hierarchy process (AHP) is proposed. The leading assumption is that for each particular decision problem and related hierarchy, AHP must not necessarily employ only one prioritization method (e.g. eigenvector method). If more available methods are used to identify the best estimates of local priorities for each comparison matrix in the hierarchy, then the estimate of final alternatives' priorities should also be the best possible, which is in natural concordance with an additive compensatory structure of the AHP synthesis. The most popular methods for deriving priorities from comparison matrices are identified as candidates (alternatives) to participate in AHP synthesis: additive normalization, eigenvector, weighted least-squares, logarithmic least-squares, logarithmic goal programming and fuzzy preference programming. Which method will be used depends on the result of multicriteria evaluation of their priority vectors' performance with regard to suggested deviation and rank reversal measures. Two hierarchies with matrices of size 3-6 are used to illustrate an approach.