Beluga whale optimization (BWO)

Beluga whale optimization (BWO) algorithm is a swarm-based metaheuristic algorithm for solving optimization problems.
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Updated 10 Jun 2022

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Beluga whale optimization (BWO) algorithm is a swarm-based metaheuristic algorithm for solving optimization problems. BWO is inspired from the behaviors of beluga whales, consisting of three phases: exploration phase, exploitation phase, and whale fall phase. The illustrating examples of some benchmark functions are provided in this website.
Main paper: Changting Zhong, Gang Li, Zeng Meng, Beluga whale optimization: A novel nature-inspired metaheuristic algorithm, Knowledge-Based Systems, 2022, 109215. doi:10.1016/j.knosys.2022.109215

Cite As

Zhong Changting (2024). Beluga whale optimization (BWO) (https://www.mathworks.com/matlabcentral/fileexchange/112830-beluga-whale-optimization-bwo), MATLAB Central File Exchange. Retrieved .

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1.0.2

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1.0.1

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1.0.0