A Full Ranking for Decision Making Units Using Ideal and Anti-Ideal Points in DEA

Abstract

We propose a procedure for ranking decision making units in data envelopment analysis, based on ideal and anti-ideal points in the production possibility set. Moreover, a model has been introduced to compute the performance of a decision making unit for these two points through using common set of weights. One of the best privileges of this method is that we can make ranking for all decision making units by solving only three programs, and also solving these programs is not related to numbers of decision making units. One of the other advantages of this procedure is to rank all the extreme and nonextreme efficient decision making units. In other words, the suggested ranking method tends to seek a set of common weights for all units to make them fully ranked. Finally, it was applied for different sets holding real data, and then it can be compared with other procedures.

Regional Spanish Tourism Competitiveness. A DEA-MONITUR approach

“…There are different techniques and proposals based on: (1) cross-efficiency DEA models (Sexton et al 1986, Doyle, Green 1994, Adler et al 2002; (2) super-efficiency models (Andersen, Petersen 1993, Zhu 1996, Seiford, Zhu 1998; and (3) virtual efficiency models (Bazargan, Vasigh 2003, Martín, Román 2006, Barzegarinegad et al 2014, Martín et al 2017). …”

Improved DEA Cross Efficiency Evaluation Method Based on Ideal and Anti-Ideal Points

“…This method efficiently restrained the second-class target level demand [7]. Barzegarinegad et al (2015) introduced a new view according to ideal and anti-ideal points concept. The new model suggested a comprehensive ranking of DMUs and sought a set of common weights for DMUs to make them fully ranked [8].…”

“…Barzegarinegad et al (2015) introduced a new view according to ideal and anti-ideal points concept. The new model suggested a comprehensive ranking of DMUs and sought a set of common weights for DMUs to make them fully ranked [8]. Lim and Zhu (2015) used CRS and VRS models to obtain the optimal weight ratio and analyzed with the Cartesian System; then they proposed a cross efficiency evaluation system based on the VRS assumption [9].…”