Electromagnetic field optimization: a physics-inspired metaheuristic optimization algorithm
This paper presents a physics-inspired metaheuristic optimization algorithm, known as Electromagnetic Field Optimization (EFO). The proposed algorithm is inspired by the behavior of electromagnets with different polarities and takes advantage of a nature-inspired ratio, known as the golden ratio. In...
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| Format: | Article |
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Elsevier
2016
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| author | Abedinpourshotorban, Hosein Shamsuddin, Siti Mariyam Beheshti, Zahra Abang Jawawi, Dayang Norhayati |
| author_facet | Abedinpourshotorban, Hosein Shamsuddin, Siti Mariyam Beheshti, Zahra Abang Jawawi, Dayang Norhayati |
| author_sort | Abedinpourshotorban, Hosein |
| collection | ePrints |
| description | This paper presents a physics-inspired metaheuristic optimization algorithm, known as Electromagnetic Field Optimization (EFO). The proposed algorithm is inspired by the behavior of electromagnets with different polarities and takes advantage of a nature-inspired ratio, known as the golden ratio. In EFO, a possible solution is an electromagnetic particle made of electromagnets, and the number of electromagnets is determined by the number of variables of the optimization problem. EFO is a population-based algorithm in which the population is divided into three fields (positive, negative, and neutral); attraction-repulsion forces among electromagnets of these three fields lead particles toward global minima. The golden ratio determines the ratio between attraction and repulsion forces to help particles converge quickly and effectively. The experimental results on 30 high dimensional CEC 2014 benchmarks reflect the superiority of EFO in terms of accuracy and convergence speed over other state-of-the-art optimization algorithms. |
| first_indexed | 2024-03-05T20:00:10Z |
| format | Article |
| id | utm.eprints-69359 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T20:00:10Z |
| publishDate | 2016 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | utm.eprints-693592017-11-22T00:45:07Z http://eprints.utm.my/69359/ Electromagnetic field optimization: a physics-inspired metaheuristic optimization algorithm Abedinpourshotorban, Hosein Shamsuddin, Siti Mariyam Beheshti, Zahra Abang Jawawi, Dayang Norhayati QA76 Computer software This paper presents a physics-inspired metaheuristic optimization algorithm, known as Electromagnetic Field Optimization (EFO). The proposed algorithm is inspired by the behavior of electromagnets with different polarities and takes advantage of a nature-inspired ratio, known as the golden ratio. In EFO, a possible solution is an electromagnetic particle made of electromagnets, and the number of electromagnets is determined by the number of variables of the optimization problem. EFO is a population-based algorithm in which the population is divided into three fields (positive, negative, and neutral); attraction-repulsion forces among electromagnets of these three fields lead particles toward global minima. The golden ratio determines the ratio between attraction and repulsion forces to help particles converge quickly and effectively. The experimental results on 30 high dimensional CEC 2014 benchmarks reflect the superiority of EFO in terms of accuracy and convergence speed over other state-of-the-art optimization algorithms. Elsevier 2016 Article PeerReviewed Abedinpourshotorban, Hosein and Shamsuddin, Siti Mariyam and Beheshti, Zahra and Abang Jawawi, Dayang Norhayati (2016) Electromagnetic field optimization: a physics-inspired metaheuristic optimization algorithm. Swarm and Evolutionary Computation, 26 . pp. 8-22. ISSN 2210-6502 http://dx.doi.org/10.1016/j.swevo.2015.07.002 DOI:10.1016/j.swevo.2015.07.002 |
| spellingShingle | QA76 Computer software Abedinpourshotorban, Hosein Shamsuddin, Siti Mariyam Beheshti, Zahra Abang Jawawi, Dayang Norhayati Electromagnetic field optimization: a physics-inspired metaheuristic optimization algorithm |
| title | Electromagnetic field optimization: a physics-inspired metaheuristic optimization algorithm |
| title_full | Electromagnetic field optimization: a physics-inspired metaheuristic optimization algorithm |
| title_fullStr | Electromagnetic field optimization: a physics-inspired metaheuristic optimization algorithm |
| title_full_unstemmed | Electromagnetic field optimization: a physics-inspired metaheuristic optimization algorithm |
| title_short | Electromagnetic field optimization: a physics-inspired metaheuristic optimization algorithm |
| title_sort | electromagnetic field optimization a physics inspired metaheuristic optimization algorithm |
| topic | QA76 Computer software |
| work_keys_str_mv | AT abedinpourshotorbanhosein electromagneticfieldoptimizationaphysicsinspiredmetaheuristicoptimizationalgorithm AT shamsuddinsitimariyam electromagneticfieldoptimizationaphysicsinspiredmetaheuristicoptimizationalgorithm AT beheshtizahra electromagneticfieldoptimizationaphysicsinspiredmetaheuristicoptimizationalgorithm AT abangjawawidayangnorhayati electromagneticfieldoptimizationaphysicsinspiredmetaheuristicoptimizationalgorithm |