Issue |
RAIRO-Oper. Res.
Volume 51, Number 1, January-March 2017
|
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Page(s) | 253 - 260 | |
DOI | https://doi.org/10.1051/ro/2016023 | |
Published online | 01 February 2017 |
Fair ranking of the decision making units using optimistic and pessimistic weights in data envelopment analysis
1 Faculty of Mathematical Sciences and Computer, Kharazmi university, Tehran, Iran.
jahanshahloomath@gmail.com; j.sadeghi1987@gmail.com
2 Department of Mathematics, Faculty of Mathematical Sciences, Shahid Beheshti University, G.C., Tehran, Iran.
mkhbakhshi@yahoo.com
Received: 19 August 2015
Accepted: 27 February 2016
Ranking all of the decision making units (DMUs) is one of the most important topics in Data envelopment analysis (DEA). Provided methods for ranking often rank the efficient units. Ranking inefficient units by early DEA models has some weaknesses since slacks are ignored. One of the methods presented in the ranking of all DMUs is Khodabakhshi and Ariavash’s method [M. Khodabakhshi and K. Ariavash, Appl. Math. Lett. 25 (2012) 2066–2070.] in this method, the maximum and minimum efficiency values of each DMU are measured by considering the sum of all efficiencies equal one. Finally, the rank of each DMU is determined in proportion to a convex combination of its minimum and maximum efficiency values. But optimistic and pessimistic weights of the other DMUs are not considered in ranking of the evaluated DMU. In this paper, a fair method to rank all DMUs, using Khodabakhshi and Ariavash’s method is proposed. In the proposed method optimistic and pessimistic efficiency values will be assessed, not only by the optimal weights of evaluated DMU but also by considering the optimistic and pessimistic optimal weights of all DMUs. The obtained optimistic and pessimistic efficiency values are supposed as criterion for the ranking. The proposed method is illustrated by a numerical example.
Mathematics Subject Classification: 90B99 / 90c05 / 90c90
Key words: Data envelopment analysis / ranking / optimistic efficiency / pessimistic efficiency
© EDP Sciences, ROADEF, SMAI 2017
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