A Multiobjective Linear Programming Approach to DEA Ranking with Common Weights

Authors

  • Mostafa Albouyeh * Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran.

https://doi.org/10.48314/ijorai.v1i1.51

Abstract

In this paper, a novel approach is proposed for determining a Common Set of Weights (CSW) through multi-objective programming within the framework of Data Envelopment Analysis (DEA). In DEA, each Decision Making Unit (DMU) is evaluated under the most favorable conditions by selecting weights that maximize its own efficiency. To ensure a fair and unified assessment across all DMUs, a model is developed to identify a CSW. The proposed model involves fractional objective functions, which are subsequently transformed into an equivalent Multi-Objective Linear Programming (MOLP) problem. To solve the MOLP, we employ either the Multi-criterion Simplex Method (MSM) or the Weighted Sum Method (WSM). Finally, the derived CSW is used to assess and rank the efficient DMUs in a consistent manner.

Keywords:

Multiple objective programming, Data envelopment analysis, Efficiency, Ranking, Common set of weights

References

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Published

2025-03-10

Issue

Vol. 1 No. 1 (2025): International Journal of Operations Research and Artificial Intelligence (IJORAI)

Section

Articles

How to Cite

Albouyeh, M. . (2025). A Multiobjective Linear Programming Approach to DEA Ranking with Common Weights. International Journal of Operations Research and Artificial Intelligence , 1(1), 1-10. https://doi.org/10.48314/ijorai.v1i1.51

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