Matrix balancing problem and binary AHP

Matrix balancing problem and binary AHP

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Article ID: iaor20084023
Country: Japan
Volume: 50
Issue: 4
Start Page Number: 515
End Page Number: 539
Publication Date: Dec 2007
Journal: Journal of the Operations Research Society of Japan
Authors: , ,
Keywords: decision theory: multiple criteria, matrices, optimization, programming: geometric
Abstract:

A matrix balancing problem and an eigenvalue problem are transformed into two minimum-norm point problems whose difference is only a norm. The matrix balancing problem is solved by scaling algorithms that are as simple as the power method of the eigenvalue problem. This study gives a proof of global convergence for scaling algorithms and applies the algorithm to Analytic Hierarchy process (AHP), which derives priority weights from pairwise comparison values by the eigenvalue method (EM) traditionally. Scaling algorithms provide the minimum χ square estimate from pairwise comparison values. The estimate has properties of priority weights such as right–left symmetry and robust ranking that are not guaranteed by the EM.

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