An integrated Data Envelopment Analysis-Artificial Neural Network-Rough Set Algorithm for assessment of personnel efficiency

Authors:
Ali Azadeh;Morteza Saberi;Reza Tavakkoli Moghaddam;Leili Javanmardi
Affiliations:
Department of Industrial Engineering and Center of Excellence for Intelligent-Based Experimental Mechanics, College of Engineering, University of Tehran, Iran;Department of Industrial Engineering, University of Tafresh, Iran and Institute for Digital Ecosystems & Business Intelligence, Curtin University of Technology, Perth, Australia;Department of Industrial Engineering and Center of Excellence for Intelligent-Based Experimental Mechanics, College of Engineering, University of Tehran, Iran;Department of Industrial Engineering and Center of Excellence for Intelligent-Based Experimental Mechanics, College of Engineering, University of Tehran, Iran
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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Abstract

Personnel specifications have greatest impact on total efficiency. They can help us to design work environment and enhance total efficiency. Determination of critical personnel attributes is a useful procedure to overcome complication associated with multiple inputs and outputs. The proposed algorithm assesses the impact of personnel efficiency attributes on total efficiency through Data Envelopment Analysis (DEA), Artificial Neural Network (ANN) and Rough Set Theory (RST). DEA has two roles in the proposed integrated algorithm of this study. It provides data ANN and finally it selects the best reduct through ANN result. Reduct is described as a minimum subset of attributes, completely discriminating all objects in a data set. The reduct selection is achieved by RST. ANN has two roles in the integrated algorithm. ANN results are basis for selecting the best reduct and it is also used for forecasting total efficiency. The proposed integrated approach is applied to an actual banking system and its superiorities and advantages are discussed.