Authors: M. Sharifi; J. Rezaeian
Addresses: Department of Industrial Engineering, Mazandaran University of Science and Technology, P.O. Box 734, Babol, Iran ' Department of Industrial Engineering, Mazandaran University of Science and Technology, P.O. Box 734, Babol, Iran
Abstract: Industrial park development is an important policy tool in many countries because the technology growth supported by parks can strengthens the industry and the economy of the country and, statistic recognising and ranking of industrial parks and zones is essential for improving industrial park development. In this paper, we evaluated efficiency of 25 industrial parks in one of the province of Iran using DEA, CCR output oriented and also the rank of DMUs using AP model for efficient DMUs in 2011-2012 and 2012-2013. Then we applied an artificial neural network and used its ability in prediction and analysed efficiency and rating of DMUs in 2012-2013 using integrated data envelopment analysis (DEA) and artificial neural networks (ANNs). Finally, the comparison between these two approaches in 2012-2013 is presented.
Keywords: data envelopment analysis; DEA; artificial neural networks; ANNs; decision making units; DMUs; efficiency evaluation; DMU efficiency; Levenberg-Marquardt training algorithm; Anderson and Peterson model; industrial parks; industrial zones; Iran.
International Journal of Industrial and Systems Engineering, 2016 Vol.23 No.1, pp.111 - 123
Available online: 06 Apr 2016 *Full-text access for editors Access for subscribers Purchase this article Comment on this article