AEFA: Artificial Electric Field Algorithm
This simulates the charge movement of AEFA
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Electrostatic Force is one of the fundamental force of physical world. The concept of electric field and charged particles provide us a strong theory for the working force of attraction or repulsion between two charged particles. In the recent years many heuristic optimization algorithms are proposed based on natural phenomenon. The current article proposes a novel artificial electric field algorithm (AEFA) which inspired by the Coulomb's law of electrostatic force. The AEFA has been designed to work as a population based optimization algorithm, the concept of charge is extended to fitness value of the population in an innovative way.
引用
Dr Anupam Yadav (2026). AEFA: Artificial Electric Field Algorithm (https://jp.mathworks.com/matlabcentral/fileexchange/71218-aefa-artificial-electric-field-algorithm), MATLAB Central File Exchange. に取得済み.
Anita, and Anupam Yadav. “AEFA: Artificial Electric Field Algorithm for Global Optimization.” Swarm and Evolutionary Computation, vol. 48, Elsevier BV, Aug. 2019, pp. 93–108, doi:10.1016/j.swevo.2019.03.013.
謝辞
ヒントを得たファイル: Gravitational Search Algorithm (GSA)
ヒントを与えたファイル: iAEFA, AEFA for Training Neural Network (GAEFA-HK)
| バージョン | 公開済み | リリース ノート | Action |
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