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Electric eel foraging optimization (EEFO) is a new optimization approach for solving optimization problems. draws inspiration from the intelligent group foraging behaviors exhibited by electric eels in nature. The algorithm mathematically models four key foraging behaviors: interaction, resting, hunting, and migration, to provide both exploration and exploitation during the optimization process. In addition, an energy factor is developed to manage the transition from global search to local search and the balance between exploration and exploitation in the search space.
W. Zhao, L. Wang, Z. Zhang, H. Fan, J. Zhang, S. Mirjalili, N. Khodadadi, Q. Cao, Electric eel foraging optimization: A new bio-inspired optimizer for engineering applications,Expert Systems With Applications, 238, (2024),122200, https://doi.org/10.1016/j.eswa.2023.122200.
The free download (before December 21, 2023) is available at:https://authors.elsevier.com/a/1i0al3PiGTPhjD
Zitieren als
W. Zhao (2026). Electric Eel Foraging Optimization (EEFO) (https://de.mathworks.com/matlabcentral/fileexchange/153461-electric-eel-foraging-optimization-eefo), MATLAB Central File Exchange. Abgerufen .
Allgemeine Informationen
- Version 1.0.2 (5,45 KB)
Kompatibilität der MATLAB-Version
- Kompatibel mit allen Versionen
Plattform-Kompatibilität
- Windows
- macOS
- Linux
| Version | Veröffentlicht | Versionshinweise | Action |
|---|---|---|---|
| 1.0.2 | Update code. |
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| 1.0.1 | Modify description. |
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| 1.0.0 |
