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All Journal Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics
Farhad Namdari
Faculty of Engineering, Lorestan University
Computer Science & IT Electrical & Electronics Engineering Engineering

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New Hybrid Non-Dominated Sorting Differential Evolutionary Algorithm Mohammad Bakhshipour; Farhad Namdari; Nooshin Bahador
Bulletin of Electrical Engineering and Informatics Vol 5, No 2: June 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (829.213 KB) | DOI: 10.11591/eei.v5i2.533

Abstract

This paper presents a new multi objective optimization algorithm with the aim of complete coverage, faster global convergence and higher solution quality. In this technique, the high-speed characteristic of particle swarm optimization (PSO) is combined with non-dominated differential evolutionary (NSDE) and an efficient multi objective optimization algorithm is created. This method posses high convergence characteristic in quite less execution times. Generating fewer populations to find the Pareto front also makes the proposed algorithm use less memory. For the purpose of performance evaluation, the algorithm is verified with four benchmarking functions on its global optimal search ability and compared with two recognized algorithm to assess its diversity. The capability of the suggested algorithm in solving practical engineering problems such as power system protection is also studied and the results are discussed in detail.
New Hybrid Non-Dominated Sorting Differential Evolutionary Algorithm Mohammad Bakhshipour; Farhad Namdari; Nooshin Bahador
Bulletin of Electrical Engineering and Informatics Vol 5, No 2: June 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (829.213 KB) | DOI: 10.11591/eei.v5i2.533

Abstract

This paper presents a new multi objective optimization algorithm with the aim of complete coverage, faster global convergence and higher solution quality. In this technique, the high-speed characteristic of particle swarm optimization (PSO) is combined with non-dominated differential evolutionary (NSDE) and an efficient multi objective optimization algorithm is created. This method posses high convergence characteristic in quite less execution times. Generating fewer populations to find the Pareto front also makes the proposed algorithm use less memory. For the purpose of performance evaluation, the algorithm is verified with four benchmarking functions on its global optimal search ability and compared with two recognized algorithm to assess its diversity. The capability of the suggested algorithm in solving practical engineering problems such as power system protection is also studied and the results are discussed in detail.
New Hybrid Non-Dominated Sorting Differential Evolutionary Algorithm Mohammad Bakhshipour; Farhad Namdari; Nooshin Bahador
Bulletin of Electrical Engineering and Informatics Vol 5, No 2: June 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (829.213 KB) | DOI: 10.11591/eei.v5i2.533

Abstract

This paper presents a new multi objective optimization algorithm with the aim of complete coverage, faster global convergence and higher solution quality. In this technique, the high-speed characteristic of particle swarm optimization (PSO) is combined with non-dominated differential evolutionary (NSDE) and an efficient multi objective optimization algorithm is created. This method posses high convergence characteristic in quite less execution times. Generating fewer populations to find the Pareto front also makes the proposed algorithm use less memory. For the purpose of performance evaluation, the algorithm is verified with four benchmarking functions on its global optimal search ability and compared with two recognized algorithm to assess its diversity. The capability of the suggested algorithm in solving practical engineering problems such as power system protection is also studied and the results are discussed in detail.
Co-Authors Mohammad Bakhshipour Nooshin Bahador