Document Type : Original Article

Authors

Department of Mathematical, Central Tehran Branch, Islamic Azad University, Tehran, Iran.

Abstract

Multi-attribute decision-making is a powerful and widely used method of solving decision-making problems and choosing the most desirable of the available options. Data envelopment analysis is a nonparametric method for calculating performance size. The basic drawback of conventional decision-making methods is that they are not capable of taking into account decision-making priorities and preferences as well as risk-taking or risk aversion. On the other hand, in some cases, it is difficult to determine the exact amount of data and the results are qualitative and quantitative. The weighted average method is classified as one of the decision-making methods that are capable of considering the priorities and subjective evaluations of the decision-maker in the decision-making process. This paper deals with one of the ranking methods in data envelopment analysis called cross-efficiency and tries to consider the decision-makers' risk-taking and risk-aversion in consolidating cross-performance matrix members as well as in the cross-efficiency integration process.

Keywords

Main Subjects

Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429-444.
Chen, Y.,Kilgour, D.M., & Hipel, K. W.,(2006). Multiple criteria classification with an application in water resources planning, Computers and operations research, pp:3301-332.
Hwang, C. L., Yoon, K.,(1981). Multiple attribute decision making, Berlin: Springer-Verlage.
Sexton, T. R., Silkman, R. H., & Hogan, A. J. (1986). Data envelopment analysis: Critique and extensions. New directions for program evaluation, 1986(32), 73-105.
Tohidi, G., Khodadadi, M. Cross-efficiency evaluation based on a interval method. International journal of data envelopment analysis, 4(2016), 1023-1030.
Wang, Y. M., Chin, K. S., & Jiang, P. (2011). Weight determination in the cross-efficiency evaluation. Computers & industrial engineering, 61(3), 497-502.
Wang, Y. M., & Parkan, C. (2005). A minimax disparity approach for obtaining OWA operator weights. Information sciences, 175(1-2), 20-29.
Yager, R. R. (1988). On ordered weighted averaging aggregation operators in multicriteria decisionmaking. IEEE transactions on systems, man, and cybernetics, 18(1), 183-190.