This conclusion is confirmed by the computational results obtained when the two models are applied to a real data set relative to the socio-economic performances of European countries and to randomly generated instances with various numbers of decision making units, inputs and outputs.
📌 3 Maddede Bu Makale
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Amaç & Hipotez:In this study, a multi-criteria data envelopment analysis (MCDEA) model, used in the literature to moderate the homogeneity of weights dispersion, is solved using pre-emptive goal programming.
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Temel Bulgular & Veri:The MCDEA model solved using pre-emptive goal programming gives the same relative efficiency as the classical DEA model while it improves the homogeneity of input-output weights.
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Sonuç & Katkı:This conclusion is confirmed by the computational results obtained when the two models are applied to a real data set relative to the socio-economic performances of European countries and to randomly generated instances with various numbers of decision making units, inputs and outputs.
In this study, a multi-criteria data envelopment analysis (MCDEA) model, used in the literature to moderate the homogeneity of weights dispersion, is solved using pre-emptive goal programming. The MCDEA model solved using pre-emptive goal programming gives the same relative efficiency as the classical DEA model while it improves the homogeneity of input-output weights. This conclusion is confirmed by the computational results obtained when the two models are applied to a real data set relative to the socio-economic performances of European countries and to randomly generated instances with various numbers of decision making units, inputs and outputs.
BAL, H., ÖRKÇÜ, H. H. (2010). A Goal Programming Approach to Weight Dispersion in Data Envelopment Analysis. Gazi University Journal of Science, Cilt: 20 - Sayı: 4, 117–125. https://ajindex.com/articles/255605
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