Enzyme action optimizer: a novel bio-inspired optimization algorithm Enzyme action optimizer: a novel bio-inspired optimization algorithm

This paper presents the enzyme action optimization (EAO) algorithm, a novel bio-inspired optimization algorithm designed to simulate the adaptive enzyme mechanism in biological systems. EAO employs a novel strategy that dynamically balances between exploration and exploitation to efficiently navigat...

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Veröffentlicht in:The Journal of supercomputing Jg. 81; H. 5; S. 686
Hauptverfasser: Rodan, Ali, Al-Tamimi, Abdel-Karim, Al-Alnemer, Loai, Mirjalili, Seyedali, Tiňo, Peter
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.04.2025
Springer Nature B.V
Schlagworte:
Adaptability
Algorithms
Benchmarks
Compilers
Computer Science
Design engineering
Design optimization
Enzymes
Exploitation
Foraging behavior
Genetic algorithms
Interpreters
Mutation
Optimization
Optimization algorithms
Principles
Processor Architectures
Programming Languages
Source code
Metaheuristic
EAO
Global optimization
Engineering design problems
Swarm intelligence optimization
Particle swarm optimization
Artificial intelligence
Optimization
Heuristic
Enzyme action optimizer
ISSN:1573-0484, 0920-8542, 1573-0484
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Zusammenfassung:This paper presents the enzyme action optimization (EAO) algorithm, a novel bio-inspired optimization algorithm designed to simulate the adaptive enzyme mechanism in biological systems. EAO employs a novel strategy that dynamically balances between exploration and exploitation to efficiently navigate and optimize complex, multi-dimensional search spaces. EAO has been tested over diverse benchmark datasets, including the 23 classical benchmark functions, IEEE CEC2017, CEC2022 benchmark functions, where it has been compared with 14 recent and highly cited optimizers. The results show the superior performance of EAO over the compared optimizers in terms of finding the optimal solution, convergence speed, robustness, and overall performance. Furthermore, EAO was applied to solve five engineering design problems and demonstrated excellent performance results. The source code of EAO is publicly available for both MATLAB at: https://www.mathworks.com/matlabcentral/fileexchange/170296-enzyme-action-optimizer-a-novel-bio-inspired-optimization and PYTHON at: https://github.com/AliRodan/Enzyme-Action-Optimizer .
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:1573-0484
0920-8542
1573-0484
DOI:10.1007/s11227-025-07052-w