Designing a New Combined Model Based on Data Envelopment Analysis, Artificial Neural Network, Genetic Algorithm and Particle Swarm Optimization to Evaluate Efficiency and Benchmarking of Efficient and Inefficient Units

Document Type : Original Article

Authors

1 Ph.D. Candidate, Central Tehran Branch, Islamic Azad University.

2 Associate Prof., Central Tehran Branch, Islamic Azad University.

3 Prof., Islamic Azad University, Tehran, Iran.

Abstract

The main purpose of the present study is to design a new hybrid model based on data envelopment analysis, artificial neural network, genetic algorithm and particle swarm optimization to evaluate the efficiency and benchmarking of efficient and inefficient units. A two stage process has been used to evaluate the relative efficiency of 16 Tavanir regional power companies, using the combined model of data envelopment analysis with the neural network optimized by genetic algorithm and using a hybrid model of particle swarm optimization with genetic algorithm Benchmarking for efficient and inefficient units has been addressed. The average efficiency of regional power companies during the years 1391 to 1396 has increased from 0.8934 to 0.91477, while the regional power companies of Azerbaijan, Isfahan, Tehran, Khorasan, Semnan, Kerman, Gilan and Yazd have always had the highest average efficiency, And West and Fars regional electric companies with average values of 0.70747 and 0.60525 have the lowest efficiency during the years 1391 to 1396.

Keywords

References

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Journal of Industrial Management Perspective
Volume 9, Issue 2 - Serial Number 34
September 2019
Pages 107-129

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