Alternative mixed integer linear programming models for identifying the most efficient decision making unit in data envelopment analysis

Authors:
Ying-Ming Wang;Peng Jiang
Affiliations:
Decision Sciences Institute, School of Public Administration, Fuzhou University, Fuzhou 350108, PR China and School of Management, Hefei University of Technology, Hefei 230009, PR China;Environmental and Biological Engineering Institute, Chongqing Technology and Business University, Chongqing 400067, PR China
Venue:
Computers and Industrial Engineering
Year:
2012

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Abstract

A mixed integer linear model for selecting the best decision making unit (DMU) in data envelopment analysis (DEA) has recently been proposed by Foroughi [Foroughi, A. A. (2011a). A new mixed integer linear model for selecting the best decision making units in data envelopment analysis. Computers and Industrial Engineering, 60(4), 550-554], which involves many unnecessary constraints and requires specifying an assurance region (AR) for input weights and output weights, respectively. Its selection of the best DMU is easy to be affected by outliers and may sometimes be incorrect. To avoid these drawbacks, this paper proposes three alternative mixed integer linear programming (MILP) models for identifying the most efficient DMU under different returns to scales, which contain only essential constraints and decision variables and are much simpler and more succinct than Foroughi's. The proposed alternative MILP models can make full use of input and output information without the need of specifying any assurance regions for input and output weights to avoid zero weights, can make correct selections without being affected by outliers, and are of significant importance to the decision makers whose concerns are not DMU ranking, but the correct selection of the most efficient DMU. The potential applications of the proposed alternative MILP models and their effectiveness are illustrated with four numerical examples.