Linear programming models for estimating weights in the analytic hierarchy process

Authors:
Bala Chandran;Bruce Golden;Edward Wasil
Affiliations:
Department of Industrial Engineering and Operations Research, University of California, Berkeley, CA;R.H. Smith School of Business, University of Maryland, College Park, MD;Kogod School of Business, American University, Washington, DC
Venue:
Computers and Operations Research
Year:
2005

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Abstract

We present an approach based on linear programming (LP) that estimates the weights for a pairwise comparison matrix generated within the framework of the analytic hierarchy process. Our approach makes sense for a number of reasons, which we discuss. We apply our LP approach to several sample problems and compare our results to those produced by other, widely used methods. In addition, we extend our linear program to include applications where the pairwise comparison matrix is constructed from interval judgments.