Finding the Most Efficient Unit in Data Envelopment Analysis (Accepted Manuscript)
محورهای موضوعی : فصلنامه ریاضی
abbas ghomashi langroudi
1
,
Masomeh abbasi maleksari
2
,
saeid shahghobadi
3
1 - Department of mathematics, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran
2 - Department of Applied Mathematics, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.
3 - Department of Applied Mathematics, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.
کلید واژه: Data envelopment analysis, Most efficient DMU, Mixed integer linear programming, ranking, Common set of weights.,
چکیده مقاله :
In data envelopment analysis, identifying the most efficient decision-making unit (DMU) is crucial for gaining insights into efficient DMUs. Various approaches have been suggested in the literature to determine the most efficient DMU in data envelopment analysis. These approaches aim to develop a model with enhanced discriminatory ability among DMUs. This study introduces a new model based on a common set of weights approach using mixed integer linear programming to select the most efficient DMU. The proposed model ensures that the efficiency score of only one DMU (the most efficient) is strictly greater than one, while the efficiency scores of other DMUs are less than or equal to one. This model demonstrates a strong discriminatory capability, enabling the full ranking of all DMUs with fewer constraints than models that allow complete ranking. To validate the proposed model and compare its performance with recent approaches, two numerical examples from the literature are utilized.
In data envelopment analysis, identifying the most efficient decision-making unit (DMU) is crucial for gaining insights into efficient DMUs. Various approaches have been suggested in the literature to determine the most efficient DMU in data envelopment analysis. These approaches aim to develop a model with enhanced discriminatory ability among DMUs. This study introduces a new model based on a common set of weights approach using mixed integer linear programming to select the most efficient DMU. The proposed model ensures that the efficiency score of only one DMU (the most efficient) is strictly greater than one, while the efficiency scores of other DMUs are less than or equal to one. This model demonstrates a strong discriminatory capability, enabling the full ranking of all DMUs with fewer constraints than models that allow complete ranking. To validate the proposed model and compare its performance with recent approaches, two numerical examples from the literature are utilized.
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