Remarks on the analytic hierarchy process
Management Science
Management Science
The Analytic Hierarchy Process--An Exposition
Operations Research
Anniversary Article: Decision Analysis in Management Science
Management Science
Combining different prioritization methods in the analytic hierarchy process synthesis
Computers and Operations Research
Data envelopment analysis for weight derivation and aggregation in the analytic hierarchy process
Computers and Operations Research
An approach to avoiding rank reversal in AHP
Decision Support Systems
Deriving priority in AHP using evolutionary computing approach
WSEAS Transactions on Information Science and Applications
One to one recommendation system for apparel online shopping
WSEAS TRANSACTIONS on SYSTEMS
Recommendation system for apparel online shopping
WSEAS TRANSACTIONS on SYSTEMS
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Need of robust multi criteria decision making techniques are becoming essential in day today life for decision makers to make appropriate decisions. This paper attempts to explore robustness through rank reversal properties of the Data Envelopment Analytic Hierarchy Process (DEAHP) in decision making. DEAHP uses the principles of Data Envelopment Analysis (DEA) to generate the local weights of elements from pairwise comparison matrices (PCM) and to compute the final weights in the Analytic Hierarchy Process (AHP). Though DEAHP was proposed relatively recently, it has been used in some practical applications by researchers worldwide. At the same time, it has also been criticised, especially on its rank reversal properties without much supporting evidence. Hence, simulation experiments were conducted to study the rank reversal properties of DEAHP, mainly drawing from similar experiments in the AHP literature. Randomly generated matrices of different sizes were used in the experiments. The results indicate that DEAHP possesses desirable rank reversal properties.