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The cooperation search algorithm (CSA) randomly generates a set of candidate solutions in the problem space, and then three operators are repeatedly executed until the stopping criterion is met: the team communication operator is used to improve the global exploration and determine the promising search area; the reflective learning operator is used to achieve a comprise between exploration and exploitation; the internal competition operator is used to choose solutions with better performances for the next cycle.
Citation pour cette source
Feng, Zhong-kai, et al. “Cooperation Search Algorithm: A Novel Metaheuristic Evolutionary Intelligence Algorithm for Numerical Optimization and Engineering Optimization Problems.” Applied Soft Computing, vol. 98, Elsevier BV, Jan. 2021, p. 106734, doi:10.1016/j.asoc.2020.106734.
Informations générales
- Version 1.0.0 (2,91 Mo)
Compatibilité avec les versions de MATLAB
- Compatible avec toutes les versions
Plateformes compatibles
- Windows
- macOS
- Linux
| Version | Publié le | Notes de version | Action |
|---|---|---|---|
| 1.0.0 |
