Document Type : Original Article

Author

Department of Mathematics, Islamic Azad University, Arak-Branch, Arak, Iran.

Abstract

One of the problems of based models on data envelopment analysis (DEA) for ranking preference voting systems is that it allows each alternative have its own weight vector. Therefore, alternatives are evaluated with different weight vectors. In this study, we propose a model based on fuzzy logic to solve the weaknesses of the previous models. This model is based on the solving of multi-objective programming models with the help of fuzzy logic, in this way it providing a vector of common weights, and finally, we can rank the alternatives.

Keywords

Main Subjects

Contreras, I. (2011). A DEA-inspired procedure for the aggregation of preferences. Expert systems with applications38(1), 564-570.
Cook, W. D., & Kress, M. (1990). A data envelopment model for aggregating preference rankings. Management science36(11), 1302-1310.
Cook, W. D., Roll, Y., & Kazakov, A. (1990). A dea model for measuring the relative eeficiency of highway maintenance patrols. INFOR: information systems and operational research28(2), 113-124.
Green, R. H., Doyle, J. R., & Cook, W. D. (1996). Preference voting and project ranking using DEA and cross-evaluation. European journal of operational research90(3), 461-472.
Hashimoto, A. (1997). A ranked voting system using a DEA/AR exclusion model: A note. European journal of operational research97(3), 600-604.
Jahanshahloo, G. R., Memariani, A., Lotfi, F. H., & Rezai, H. Z. (2005). A note on some of DEA models and finding efficiency and complete ranking using common set of weights. Applied mathematics and computation166(2), 265-281.
Kahraman, C. (Ed.). (2008). Fuzzy multi-criteria decision making: theory and applications with recent developments(Vol. 16). Springer Science & Business Media.
Kornbluth, J. S. H. (1991). Analysing policy effectiveness using cone restricted data envelopment analysis. Journal of the operational research society42(12), 1097-1104.
Noguchi, H., Ogawa, M., & Ishii, H. (2002). The appropriate total ranking method using DEA for multiple categorized purposes. Journal of computational and applied mathematics146(1), 155-166.
Obata, T., & Ishii, H. (2003). A method for discriminating efficient candidates with ranked voting data. European Journal of operational research151(1), 233-237.
Roll, Y., Cook, W. D., & Golany, B. (1991). Controlling factor weights in data envelopment analysis. IIE transactions23(1), 2-9.
Thompson, R. G., Singleton Jr, F. D., Thrall, R. M., & Smith, B. A. (1986). Comparative site evaluations for locating a high-energy physics lab in Texas. Interfaces16(6), 35-49.