A compromise solution approach for finding common weights in DEA: an improvement to Kao and Hung's approach

M Zohrehbandian (), A Makui and A Alinezhad
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M Zohrehbandian: Islamic Azad University – Karaj Branch
A Makui: Iran University of Science & Technology
A Alinezhad: Islamic Azad University – Qazvin Branch

Journal of the Operational Research Society, 2010, vol. 61, issue 4, 604-610

Abstract: Abstract Data envelopment analysis (DEA) is the leading technique for measuring the relative efficiency of decision-making units (DMUs) on the basis of multiple inputs and multiple outputs. In this technique, the weights for inputs and outputs are estimated in the best advantage for each unit so as to maximize its relative efficiency. But, this flexibility in selecting the weights deters the comparison among DMUs on a common base. For dealing with this difficulty, Kao and Hung (2005) proposed a compromise solution approach for generating common weights under the DEA framework. The proposed multiple criteria decision-making (MCDM) model was derived from the original non-linear DEA model. This paper presents an improvement to Kao and Hung's approach by means of introducing an MCDM model which is derived from a new linear DEA model.

Keywords: MOLP; compromise solution; DEA; efficiency; ranking; weight restrictions (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (21)

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DOI: 10.1057/jors.2009.4

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