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2014•arXiv (Cornell University)Open access

Decision Making via AHP

M. Andrecut

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Abstract

The Analytic Hierarchy Process (AHP) is a procedure for establishing priorities in multi-criteria decision making problems. Here we discuss the Logarithmic Least Squares (LLS) method for the AHP and group-AHP, which provides an exact and unique solution for the priority vector. Also, we show that for the group-AHP, the LLS method is equivalent with the minimization of the weighted sum of generalized Kullback-Leibler divergences, between the group-priority vector and the priority vector of each expert.

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The Analytic Hierarchy Process (AHP) is a procedure for establishing priorities in multi-criteria decision making problems. Here we discuss the Logarithmic Least Squares (LLS) method for the AHP and group-AHP, which provides an exact and unique solution for the priority vector. Also, we show that for the group-AHP, the LLS method is equivalent with the minimization of the weighted sum of generalized Kullback-Leibler divergences, between the group-priority vector and the priority vector of each expert.

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Available abstract

The Analytic Hierarchy Process (AHP) is a procedure for establishing priorities in multi-criteria decision making problems. Here we discuss the Logarithmic Least Squares (LLS) method for the AHP and group-AHP, which provides an exact and unique solution for the priority vector. Also, we show that for the group-AHP, the LLS method is equivalent with the minimization of the weighted sum of generalized Kullback-Leibler divergences, between the group-priority vector and the priority vector of each expert.

Key concepts: Analytic hierarchy process, Logarithm, Group decision-making, Computer science, Group (periodic table), Operations research, Hierarchy, Mathematical optimization

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