Title: Application of linear programming to derive the local weight in the analytic hierarchy process
Abstract: The analytic hierarchy process (AHP) has become more developed in both the areas of theory and practice. The important topic here, is how to drive the local weight vector from a pairwise reciprocal matrix. In the literature, there are several methods used to accomplish this. Most recently, Hosseinian et al. (2009) suggested the LP-GW-AHP because it obviously provides better weights. In this article, the LP-GW-AHP method is applied to multi-level decision problems, and the weights were compared with Saaty's eigenvector. According to our findings, of the LP-GW-AHP method, Saaty's eigenvector method differs slightly from that derived in the local weight values.
Publication Year: 2016
Publication Date: 2016-01-01
Language: en
Type: article
Indexed In: ['crossref']
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Cited By Count: 1
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