A common-weight MCDM framework for decision problems with multiple inputs and outputs


KARSAK E. E. , Ahiska S. S.

International Conference on Computational Science and Its Applications (ICCSA 2007), Kuala-Lumpur, Malaysia, 26 - 29 August 2007, vol.4705, pp.779-781 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 4705
  • City: Kuala-Lumpur
  • Country: Malaysia
  • Page Numbers: pp.779-781

Abstract

This paper presents a common weight multi-criteria decision making (MCDM) approach for determining the best decision making unit (DMU) taking into consideration multiple inputs and outputs. Its robustness and discriminating power are illustrated through comparing the results with those obtained by data envelopment analysis (DEA) and its extensions such as cross efficiency analysis and minimax efficiency DEA model, which yield a ranking with an improved discriminating power. Several examples reported in earlier research addressing DEA's discriminating power are used to illustrate the application of the proposed approach. The results indicate that the proposed framework enables further ranking of DEA-efficient DMUs with a notable saving in the number of mathematical programming models solved.