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Ishizaka, A. (2012). Clusters and pivots for evaluating a large number of alternatives in AHP. Pesquisa Operacional, 31(1), 87–101. 
Added by: Klaus D. Goepel (07 Jun 2019 06:59:02 Asia/Singapore)   Last edited by: Klaus-admin (08 Jun 2019 03:11:19 Asia/Singapore)
Resource type: Journal Article
BibTeX citation key: Ishizaka2012
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Categories: AHP/ANP
Keywords: alternatives, Analytic Hierarchy Process (AHP), cluster, pivot
Creators: Ishizaka
Collection: Pesquisa Operacional
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Abstract
AHP has been successful in many cases but it has a major limitation: a larger number of alternatives requires a high number of judgements in the comparison matrices. In order to reduce this problem, we present a method with clusters and pivots. This method also helps with a further four problems of the Analytic Hierarchy Process. It enlarges the comparison scale, facilitates the construction of a consistent or near consistent matrix, eliminates the problem of the choice of the priorities derivation method and allows the use of incomparable alternatives.
  
Notes
For each criterion the alternatives are preordered. Alternatives are divided into clusters. Comparisons are entered in clustered matrices and priorities are calculated. Priorities of the clusters are joined with a common element: “the pivot”.
  
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