Title: Implementation of data envelopment analysis–genetic algorithm for improved performance assessment of transmission units in power industry

Authors: Ali Azadeh, Sayed Mohammad Asadzadeh, Somayeh Ahmadi Movaghar

Addresses: Department of Industrial Engineering, Department of Engineering Optimization Research, Center of Excellence for Intelligent Based Mechanical Experiments, College of Engineering, University of Tehran, P.O. Box 14178-43111, Tehran, Iran. ' Department of Industrial Engineering, Department of Engineering Optimization Research, Center of Excellence for Intelligent Based Mechanical Experiments, College of Engineering, University of Tehran, P.O. Box 14178-43111, Tehran, Iran. ' Department of Industrial Engineering, Department of Engineering Optimization Research, Center of Excellence for Intelligent Based Mechanical Experiments, College of Engineering, University of Tehran, P.O. Box 14178-43111, Tehran, Iran

Abstract: This paper introduces a hybrid approach based on data envelopment analysis (DEA) and genetic algorithm (GA) for efficiency assessment and optimisation of electricity transmission units. The optimisation procedure in this paper is followed from two different viewpoints, that is, input efficiency and input cost. The result of DEA model is verified and validated by GA through Spearman correlation experiment. Moreover, the proposed approach uses the measure specific super-efficiency DEA model for sensitivity analysis to determine the critical inputs based on efficiency and cost allocation super-efficiency DEA model to determine the critical inputs based on cost. The unique feature of this study is utilisation of GA and DEA for assessment and optimisation of critical inputs from two different viewpoints: efficiency and cost. This is the first study that introduces a hybrid GA–DEA approach for performance assessment and optimisation of electricity transmission units. The superiority of the hybrid approach is shown for 32 transmission units.

Keywords: performance assessment; optimisation; GAs; genetic algorithms; electricity transmission units; power systems; data envelopment analysis; DEA; efficiency; cost allocation.

DOI: 10.1504/IJISE.2011.040767

International Journal of Industrial and Systems Engineering, 2011 Vol.8 No.1, pp.83 - 103

Published online: 31 Jan 2015 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article