A LINEAR GOAL PROGRAMMING MODEL FOR CALCULATING COMMON WEIGHTS IN DATA ENVELOPMENT ANALYSIS PROBLEMS
J Salehi Sedghiani, Maghsoud Amiri, Seyed Hadi Razavi, Shide Sadat Hashemi, As’hab Habibzadeh
Abstract
J Salehi Sedghiani, Maghsoud Amiri, Seyed Hadi Razavi, Shide Sadat Hashemi, As’hab Habibzadeh
Abstract
Data Envelopment Analysis (DEA) is a wide range of mathematical models that used for measuring the relative efficiency of a set of harmonic units whit similar inputs and outputs. This model calculates some different weight for input and output variables in each decision making model. This variation in similar weights caused some critiques to this method. From 1991 some linear and nonlinear models proposed to calculate a common set of weights for decision making units in DEA models. In this article also suggests a linear goal programming approach for this purpose and its application compared with other models in a numerical example. Linearity, applicability and meaningfully of estimated weights are some benefits of suggested model.
OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Data Envelopment Analysis (DEA) is a wide range of mathematical models that used for measuring the relative efficiency of a set of harmonic units whit similar inputs and outputs. This model calculates some different weight for input and output variables in each decision making model. This variation in similar weights caused some critiques to this method. From 1991 some linear and nonlinear models proposed to calculate a common set of weights for decision making units in DEA models. In this article also suggests a linear goal programming approach for this purpose and its application compared with other models in a numerical example. Linearity, applicability and meaningfully of estimated weights are some benefits of suggested model.
Key concepts: Data envelopment analysis, Goal programming, Linear programming, Computer science, Operations research, Mathematical optimization, Econometrics, Mathematics