Presenting a data envelopment analysis model based on Goal programming and weight Restriction in order to evaluate the efficiency and ranking of decision-making units in Ghavamin Bank

Document Type : Research Paper


1 Ph.D. Candidate, Industrial Management with the Field of Operational Research, Faculty of Economics and Management, Science and Research Branch, Islamic Azad University,Tehran Iran.

2 Prof., Department of Industrial Management, Faculty of Economics and Management, Science and Research Branch, Islamic Azad University, Tehran, Iran.

3 Associate Prof., Department of Industrial Management, Faculty of Economics and Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran.


Objective: The purpose of this paper is to evaluate the efficiency of decision-making units using the goal programming model of data envelopment analysis with restriction weight and ranking of units with a unique method in Ghavamin Bank.
Methods: In this study, the classical CCR model was used to determine the management efficiency of provincial branches in Ghavamin Bank. To increase the discriminative power of efficient and inefficient decision-making units, a combination of goal programming models with Weight restriction was used and a new model called goal programming of data envelopment analysis with Weight restriction was presented.
Results: Based on the output values of the classical CCR model, 16 out of 32 decision-making units became efficient and 16 units became inefficient. In the next step, for more separability of the units, the goal programming model of data envelopment analysis with Weight restriction was used. The results of the first-order Euclidean norm became 7 efficient and the rest inefficient out of 32 decision-making units, and the results of the infinite Euclidean norm became 1 of 32 efficient units and the rest of the decision-making units inefficient.
Conclusion: The results showed that the goal programming model of data envelopment analysis with Weight restriction related to infinite Euclidean norm in separating and ranking efficient decision-making units from inefficient has a high discriminate power compared to the classical CCR model and the first-order Euclidean norm


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