A multi-strategy improved electric eel foraging optimization algorithm: continuous and binary variants for solving optimization problems

Electric Eel Foraging Optimization (EEFO) algorithm is a metaheuristic inspired by the social predation behavior of electric eels. It incorporates interactions, resting, migration, and hunting activities to enhance search efficiency. Although EEFO is effective for optimization tasks, it is character...

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Veröffentlicht in:	International journal of machine learning and cybernetics Jg. 16; H. 9; S. 5985 - 6030
Hauptverfasser:	Mostafa, Reham R., Khedr, Ahmed M., AL Aghbari, Zaher, Afyouni, Imad, Kamel, Ibrahim, Ahmed, Naveed
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2025 Springer Nature B.V
Schlagworte:	Algorithms Artificial Intelligence Classification Complex Systems Computational Intelligence Control Datasets Design engineering Energy consumption Engineering Evolutionary computation Exploitation Foraging behavior Genetic algorithms Global optimization Heuristic Heuristic methods Mapping Mechatronics Mutation Optimization algorithms Optimization techniques Original Article Pattern Recognition Physics Rank tests Robotics Searching Space exploration Strategy Systems Biology Metaheuristic Electric eel foraging optimization (EEFO) Real-world optimization problems Optimization Differential evolution (DE)
ISSN:	1868-8071, 1868-808X
Online-Zugang:	Volltext
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