AEFA: Artificial Electric Field Algorithm

Version 1.0.0 (27,7 ko) par Dr Anupam Yadav

This simulates the charge movement of AEFA

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Mise à jour 15 avr. 2019

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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.

Citation pour cette source

Dr Anupam Yadav (2026). AEFA: Artificial Electric Field Algorithm (https://fr.mathworks.com/matlabcentral/fileexchange/71218-aefa-artificial-electric-field-algorithm), MATLAB Central File Exchange. Extrait(e) le janvier 13, 2026.

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.

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Créé avec R2019a

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Inspiré par : Gravitational Search Algorithm (GSA)

A inspiré : iAEFA, AEFA for Training Neural Network (GAEFA-HK)

Version	Publié le	Notes de version
1.0.0	15 avr. 2019		Zip Toolbox

MLA	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.
APA	Anita, & Yadav, A. (2019). AEFA: Artificial electric field algorithm for global optimization. Swarm and Evolutionary Computation, 48, 93–108. Elsevier BV. Retrieved from https://doi.org/10.1016%2Fj.swevo.2019.03.013
BibTeX	@article{Anita_2019, doi = {10.1016/j.swevo.2019.03.013}, url = {https://doi.org/10.1016%2Fj.swevo.2019.03.013}, year = 2019, month = {aug}, publisher = {Elsevier {BV}}, volume = {48}, pages = {93--108}, author = {Anita and Anupam Yadav}, title = {{AEFA}: Artificial electric field algorithm for global optimization}, journal = {Swarm and Evolutionary Computation} }