A Common Weight Multi-criteria Decision analysis-data Envelopment Analysis Approach with Assurance Region for Weight Derivation from Pairwise Comparison Matrices

Abstract

Deriving weights from a pairwise comparison matrix (PCM) is a subject for which a wide range of methods have ever been presented. This paper proposes a common weight multi criteria decision analysis-data envelopment analysis (MCDA-DEA) approach with assurance region for weight derivation from a PCM. The proposed model has several merits over the competing approaches and removes the drawbacks of the well-known DEAHP and DEA/AR methods. Some numerical examples are provided from the literature in order to confirm the merits of the proposed method and its applications in multi criteria decision making. Results disclose the advantages of the proposed approach.