A novel Kangaroo Escape Optimizer: Weight Function Example
Versión 1.0.0 (16,6 KB) por
Abdullah M. Shaheen
A novel Kangaroo Escape Optimizer designed for Weight Function Example
This study introduces a novel Kangaroo Escape Algorithm (KEA), that parallels the survival-driven escape behaviors of Kangaroos integrating adaptive energy control and chaotic perturbation to achieve an effective balance between exploration and exploitation. Unlike conventional algorithms that rely on multiple tuning parameters, KEA operates with only two user-defined settings, offering a simplified yet highly efficient optimization framework. It uses zigzag escape and long jump escape models, with a unique decoy drop mechanism to improve solution diversity and avoid premature convergence.
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[1] A. S. Aljumah, M. H. Alqahtani, A. R. Ginidi, and A. M. Shaheen, “A novel Kangaroo Escape Algorithm for efficient combined heat and power economic dispatch: Feasibility analysis and validations,” Energy Reports, vol. 14, pp. 2535–2556, Dec. 2025, doi: 10.1016/J.EGYR.2025.09.016.
[2] S. Z. A. M. and A. Shaheen, “A Kangaroo Escape Optimizer-Enabled Fractional-Order PID Controller for Enhancing Dynamic Stability in Multi-Area Power Systems,” Fractal Fract., vol. 9, no. 8, p. 530, 2025, doi: https://doi.org/10.3390/fractalfract9080530.
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R2025b
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| Versión | Publicado | Notas de la versión | |
|---|---|---|---|
| 1.0.0 |