DEA with Common Set of Weights Based on a Multi Objective Fractional Programming problem

Seyyed Hossein Razavi Hajiagha; Shide Sadat Hashemi; Hannan Amoozad Mahdiraji

DEA with Common Set of Weights Based on a Multi Objective Fractional Programming problem

Seyyed Hossein Razavi Hajiagha, Shide Sadat Hashemi, Hannan Amoozad Mahdiraji

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Abstract

Data envelopment analysis operates as a tool to appraise the relative
efficiency of a set of homogenous decision making units. DEA allows each DMU to take its optimal weight in comparison toother DMUs while a similar condition is considered for other units. This feature threats the comparability of different units because different weighting schemes are used for different DMUs. In this paper, a model is presented to determine a common set of weights to calculate DMUs efficiency. This model is developed based on a multi objective fractional linear programming model that considers the original DEA's results as ideal solution an
d seeks a set of common weights to evaluate DMUs and increases the model's discrimination power. A numerical example is solved and the proposed method's results are compared to some previous methods. This Comparison has shown the proposed method's advantages in ranking DMUs

Original language	English
Pages (from-to)	207-214
Number of pages	8
Journal	International Journal of Industrial Engineering & Production Research (IJIEPR)
Volume	25
Issue number	3
Publication status	Published - 1 Sep 2014
Externally published	Yes

Bibliographical note

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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title = "DEA with Common Set of Weights Based on a Multi Objective Fractional Programming problem",

abstract = "Data envelopment analysis operates as a tool to appraise the relative efficiency of a set of homogenous decision making units. DEA allows each DMU to take its optimal weight in comparison toother DMUs while a similar condition is considered for other units. This feature threats the comparability of different units because different weighting schemes are used for different DMUs. In this paper, a model is presented to determine a common set of weights to calculate DMUs efficiency. This model is developed based on a multi objective fractional linear programming model that considers the original DEA's results as ideal solution and seeks a set of common weights to evaluate DMUs and increases the model's discrimination power. A numerical example is solved and the proposed method's results are compared to some previous methods. This Comparison has shown the proposed method's advantages in ranking DMUs",

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N2 - Data envelopment analysis operates as a tool to appraise the relative efficiency of a set of homogenous decision making units. DEA allows each DMU to take its optimal weight in comparison toother DMUs while a similar condition is considered for other units. This feature threats the comparability of different units because different weighting schemes are used for different DMUs. In this paper, a model is presented to determine a common set of weights to calculate DMUs efficiency. This model is developed based on a multi objective fractional linear programming model that considers the original DEA's results as ideal solution and seeks a set of common weights to evaluate DMUs and increases the model's discrimination power. A numerical example is solved and the proposed method's results are compared to some previous methods. This Comparison has shown the proposed method's advantages in ranking DMUs

AB - Data envelopment analysis operates as a tool to appraise the relative efficiency of a set of homogenous decision making units. DEA allows each DMU to take its optimal weight in comparison toother DMUs while a similar condition is considered for other units. This feature threats the comparability of different units because different weighting schemes are used for different DMUs. In this paper, a model is presented to determine a common set of weights to calculate DMUs efficiency. This model is developed based on a multi objective fractional linear programming model that considers the original DEA's results as ideal solution and seeks a set of common weights to evaluate DMUs and increases the model's discrimination power. A numerical example is solved and the proposed method's results are compared to some previous methods. This Comparison has shown the proposed method's advantages in ranking DMUs

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JF - International Journal of Industrial Engineering and Production Research

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