An integrated DEA–COLS–SFA algorithm for optimization and policy making of electricity distribution units

This paper presents an integrated data envelopment analysis (DEA)–corrected ordinary least squares (COLS)–stochastic frontier analysis (SFA)–principal component analysis (PCA)–numerical taxonomy (NT) algorithm for performance assessment, optimization and policy making of electricity distribution units. Previous studies have generally used input–output DEA models for benchmarking and evaluation of electricity distribution units. However, this study proposes an integrated flexible approach to measure the rank and choose the best version of the DEA method for optimization and policy making purposes. It covers both static and dynamic aspects of information environment due to involvement of SFA which is finally compared with the best DEA model through the Spearman correlation technique. The integrated approach would yield in improved ranking and optimization of electricity distribution systems. To illustrate the usability and reliability of the proposed algorithm, 38 electricity distribution units in Iran have been considered, ranked and optimized by the proposed algorithm of this study.