Electromagnetic Field Optimization a physics-inspired metaheuristic optimization algorithm
Electromagnetic Field Optimization (EFO) is a physics-inspired metaheuristic optimization algorithm. 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. This version is designed to work with CEC 2014 benchmarks for evaluation.
Cite As
hosein abedinpourshotorban (2024). Electromagnetic Field Optimization a physics-inspired metaheuristic optimization algorithm (https://www.mathworks.com/matlabcentral/fileexchange/52744-electromagnetic-field-optimization-a-physics-inspired-metaheuristic-optimization-algorithm), MATLAB Central File Exchange. Retrieved .
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- Mathematics and Optimization > Global Optimization Toolbox > Multiobjective Optimization >
- Sciences > Physics >
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Electromagnetic Field Optimization a physics-inspired metaheuristic optimization algorithm/
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