Title: A DEA-PROMETHEE approach for complete ranking of units

Authors: Maryam Bagherikahvarin

Addresses: SMG Unit, Computer and Decision Engineering Department, Ecole polytechnique de Bruxelles, Université Libre de Bruxelles, Boulevard du Triomphe CP 210-01, 1050 Bruxelles, Brussels, Belgium

Abstract: Data envelopment analysis (DEA) and multiple criteria decision aid (MCDA) are two well-known approaches to rank so-called decision-making units (DMUs) or alternatives. In this contribution, a two-step model is presented to completely rank units according to multiple inputs and outputs. In the first step, DEA is applied between each pair of DMUs independently to generate a pairwise comparison matrix. In the second step, the obtained matrix is exploited by means of Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) to completely rank units. We show the compatibility between the resulting ranking of DEA and DEA-PROMETHEE methods while there exist just one input and one output. We also discuss the monotonicity property of the method. We compare DEA-PROMETHEE with an integrated DEA-AHP approach on a numerical example.

Keywords: data envelopment analysis; DEA; multiple criteria decision aid; MCDA; PROMETHEE; efficiency; ranking; decision-making; DM.

DOI: 10.1504/IJOR.2019.100726

International Journal of Operational Research, 2019 Vol.35 No.2, pp.224 - 244

Received: 31 Mar 2016
Accepted: 25 Jun 2016
Published online: 17 Jul 2019 *

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