Paper Info
Title
A new data envelopment analysis method for priority determination and group decision making in the analytic hierarchy process
Abstract
The DEAHP method for weight deviation and aggregation in the analytic hierarchy process (AHP) has been found flawed and sometimes produces counterintuitive priority vectors for inconsistent pairwise comparison matrices, which makes its application very restrictive. This paper proposes a new data envelopment analysis (DEA) method for priority determination in the AHP and extends it to the group AHP situation. In this new DEA methodology, two specially constructed DEA models that differ from the DEAHP model are used to derive the best local priorities from a pairwise comparison matrix or a group of pairwise comparison matrices no matter whether they are perfectly consistent or inconsistent. The new DEA method produces true weights for perfectly consistent pairwise comparison matrices and the best local priorities that are logical and consistent with decision makers (DMs)’ subjective judgments for inconsistent pairwise comparison matrices. In hierarchical structures, the new DEA method utilizes the simple additive weighting (SAW) method for aggregation of the best local priorities without the need of normalization. Numerical examples are examined throughout the paper to show the advantages of the new DEA methodology and its potential applications in both the AHP and group decision making.
Year
DOI
Venue
2009
10.1016/j.ejor.2008.01.049
European Journal of Operational Research
Keywords
Field
DocType
Data envelopment analysis,Analytic hierarchy process,DEAHP,Group decision making,Multiple criteria decision making
Data mining,Pairwise comparison,Logical conjunction,Mathematical optimization,Weighting,Matrix (mathematics),Decision support system,Data envelopment analysis,Analytic hierarchy process,Operations management,Mathematics,Group decision-making
Journal
Volume
Issue
ISSN
195
1
0377-2217
Citations 
PageRank 
References 
21
1.30
2
Authors
2
Name
Order
Citations
PageRank
Ying-Ming Wang13256166.96
Kwai-Sang Chin2103354.69