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| Autore principale: | |
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| Natura: | Recurso digital |
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Zenodo
2025
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| Accesso online: | https://doi.org/10.5281/zenodo.15526530 |
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Sommario:
- <p>Abstract- In this paper, we proposed a hybrid <br>approach <br>that <br>combines <br>the <br>Whale <br>Optimization Algorithm (WOA) with the <br>Particle Swarm Optimization (PSO) algorithm. <br>Using this hybridization, this paper achieved a <br>balance between exploration and exploitation. <br>By combining the strengths of both <br>algorithms, this hybrid approach enhances <br>solution accuracy and convergence speed. To <br>evaluate its effectiveness, this paper tested the <br>hybrid model using a total of 23 benchmark <br>functions, which provided insights into its <br>performance across various optimization</p> <p>scenarios.This review explores WOA and its</p> <p>hybrid variations,discussing their improvements. </p>