A comparative analysis of the DEA-CCR model and the VIKOR method
DOI:
https://doi.org/10.2298/YJOR0802187OKeywords:
multi criteria, decision making, data envelopment analysis, compromiseAbstract
Data Envelopment Analysis (DEA) introduces a model for weights determination maximizing efficiency of the decision-making units. The primary focus of the DEA model is to compare decision-making units (alternatives) in terms of their efficiency in converting inputs into outputs. The multicriteria decision making (MCDM) method VIKOR uses a common set of weights expressing a decision maker's preferences. In contrast, the CCR model of DEA does not provide a common set of weights that could express the preferences of a decision maker. The weights in MCDM do not have a clear economic significance, but their use provides the opportunity to model the real aspects of decision making, such as the preference structure. A comparison of DEA and MCDM shows that DEA resembles MCDM, but the results differ. In spite of these differences, DEA could be used as a supplement for screening alternatives within MCDM. An application of DEA and MCDM is illustrated by an example of hydropower system planning.References
Adler, N., and Golany, B., “Including principal component weights to improve discrimination in data envelopment analysis”, Journal of the Operational Research Society, 53(9) (2002) 985-991.
Amin, G.R., Toloo, M., and Sohrabi, B., “An improved MCDM DEA model for technology selection”, International Journal of Production Research, 44(13) (2006) 2681-2686.
Andersen, P., and Petersen, N.C., “A procedure for ranking efficient units in data envelopment analysis”, Management Science, 39 (1993) 1261–1264.
Angulo-Meza, L., and Lins, M.P.E., “Review of methods for increasing discrimination in data envelopment analysis”, Annals of Operations Research, 116 (2002) 225–242.
Bouyssou, D., “Using DEA as a tool for MCDM: some remarks”, Journal of the Operational Research Society, 50(9) (1999) 974-978.
Charnes, A., Cooper, W., and Rhodes, E., “Measuring the efficiency of decision making units”, European Journal of Operational Research, 2 (1978) 429-444.
Ciang, C.I., and Tzeng, G.H., “A multiple objective programming approach to data envelopment analysis”, in: Y., Shi, and M., Zeleny, (eds.), New Frontiers of Decision Making for the Information Technology Era, World Scientific, Singapore, 2000.
Doyle, J., and Green, R., “Data envelopment analysis and multiple criteria decision making”, Omega, 21 (1993) 713-715.
Duckstein, L., and Opricovic, S., “Multiobjective optimization in river basin development”, Water Resources Research, 16 (1980) 14-20.
Dyson, R.G., Thanassoulis, E., and Boussofiane, A., “Data envelopment analysis”, in: Tutorial Papers in Operational Research, Operational Research Society, 1990.
Frontier Analyst, Banxia Software Ltd, Glasgow, 2000.
Goel, T., Vaidyanathan, R., Haftka, R.T., Shyy, W., Queipo, N.V., and Tucker, K., “Response surface approximation of Pareto optimal front in multi-objective optimization”, Comput. Methods Appl. Mech. Engrg., 196 (2007) 879-893.
Green, R., Doyle, J.R., and Cook, W.D., “Preference voting and project ranking using DEA and cross-evaluation”, European Journal of Operational Research, 90 (1996) 461-472.
Halme, M., and Korhonen, P., “Restricting weights in value efficiency analysis”, European Journal of Operational Research, 126 (2000) 175-188.
Halme, M., Joro, T., Korhonen, P., Salo, S., and Wallenius, J., “Value efficiency analysis for incorporating preference information in DEA”, Management Science, 45 (2000) 103-115.
Joro, T., Korhonen, P., and Wallenius, J., “Structural comparison of data envelopment analysis and multiple objective linear programming”, Management Science, 44 (1998) 962-970.
Korhonen, P., Siljamäki, A., and Soismaa, M., “On the use of value efficiency analysis and some further developments”, Journal of Productivity Analysis, 17 (2002) 49-64.
Li, X.B., and Reeves, G.R., “A multiple criteria approach to data envelopment analysis”, European Journal of Operational Research, 115 (1999) 507-517.
Opricovic, S., and Tzeng, G.H., “Extended VIKOR method in comparison with outranking methods”, European Journal of Operational Research, 178 (2) (2007) 514-529.
Parkan, C., and Wu, M.L., “Comparison of three modern multicriteria decision-making tools”, International Journal of Systems Science, 31(4) (2000) 497-517.
Roll, Y., Cook, W., and Golany, B., “Controlling factor weights in DEA”, IIE Transactions, 23 (1991) 2–9.
Sarkis, J., “A comparative analysis of DEA as a discrete alternative multiple criteria decision tool”, European Journal of Operational Research, 123 (2000) 543-557.
Sinuany-Stern, Z., Mehrez, A., and Hadad, Y., “An AHP/DEA methodology for ranking decision making units”, Intl. Trans. in Op. Res., 7 (2000) 109-124.
Stewart, T., “Relationships between data envelopment analysis and multicriteria decision analysis”, Journal of the Operational Research Society, 47 (1996) 654-665.
Sueyoshi, T., “DEA-Discriminant Analysis: Methodological comparison among eight discriminant analysis approaches”, European Journal of Operational Research, 169 (2006) 247–272.
Takeda, E., and Satoh, J., “A data envelopment analysis approach to multicriteria decision problems with incomplete information”, Computers and Mathematics with Applications, 39 (2000) 81-90.
Tone, K., “A slacks-based measure of efficiency in data envelopment analysis”, European Journal of Operational Research, 130 (2001) 498-509.
Wiecek, M.M., “Multiple criteria decision making for engineering” (Editorial), Omega, 36 (2008) 337-339.
Zhu, J., “Data envelopment analysis with preference structure”, Journal of the Operational Research Society, 47 (1996) 136-150.
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