Contreras, I. (2011). A DEA-inspired procedure for the aggregation of preferences. Expert systems with applications, 38(1), 564-570.
Cook, W. D., & Kress, M. (1990). A data envelopment model for aggregating preference rankings. Management science, 36(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 research, 28(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 research, 90(3), 461-472.
Hashimoto, A. (1997). A ranked voting system using a DEA/AR exclusion model: A note. European journal of operational research, 97(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 computation, 166(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 society, 42(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 mathematics, 146(1), 155-166.
Obata, T., & Ishii, H. (2003). A method for discriminating efficient candidates with ranked voting data. European Journal of operational research, 151(1), 233-237.
Roll, Y., Cook, W. D., & Golany, B. (1991). Controlling factor weights in data envelopment analysis. IIE transactions, 23(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. Interfaces, 16(6), 35-49.
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