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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Vydané v:	International journal of machine learning and cybernetics Ročník 16; číslo 9; s. 5985 - 6030
Hlavní autori:	Mostafa, Reham R., Khedr, Ahmed M., AL Aghbari, Zaher, Afyouni, Imad, Kamel, Ibrahim, Ahmed, Naveed
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2025 Springer Nature B.V
Predmet:	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
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