Paper Info
Title
A linear programming method for generating the most favorable weights from a pairwise comparison matrix
Abstract
This paper proposes a linear programming method for generating the most favorable weights (LP-GFW) from pairwise comparison matrices, which incorporates the variable weight concept of data envelopment analysis (DEA) into the priority scheme of the analytic hierarchy process (AHP) to generate the most favorable weights for the underlying criteria and alternatives on the basis of a crisp pairwise comparison matrix. The proposed LP-GFW method can generate precise weights for perfectly consistent pairwise comparison matrices and approximate weights for inconsistent pairwise comparison matrices, which are not too far from Saaty's principal right eigenvector weights. The issue of aggregation of local most favorable weights and rank preservation methods is also discussed. Four numerical examples are examined using the LP-GFW method to illustrate its potential applications and significant advantages over some existing priority methods.
Year
DOI
Venue
2008
10.1016/j.cor.2007.05.002
Computers & OR
Keywords
DocType
Volume
LP-GFW method,existing priority method,proposed LP-GFW method,pairwise comparison matrix,rank preservation method,crisp pairwise comparison matrix,linear programming method,consistent pairwise comparison matrix,inconsistent pairwise comparison matrix,favorable weight
Journal
35
Issue
ISSN
Citations 
12
Computers and Operations Research
11
PageRank 
References 
Authors
1.19
13
3
Name
Order
Citations
PageRank
Ying-Ming Wang13256166.96
Celik Parkan229416.66
Ying Luo346720.48