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AEFA: Artificial Electric Field Algorithm

version 1.0.0 (27.7 KB) by Anupam Yadav
This simulates the charge movement of AEFA

15 Downloads

Updated 15 Apr 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.

Cite As

Anupam Yadav (2021). AEFA: Artificial Electric Field Algorithm (https://www.mathworks.com/matlabcentral/fileexchange/71218-aefa-artificial-electric-field-algorithm), MATLAB Central File Exchange. Retrieved .

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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MATLAB Release Compatibility
Created with R2019a
Compatible with any release
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Acknowledgements

Inspired by: Gravitational Search Algorithm (GSA)

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