The whale optimization algorithm is a new group intelligence optimization algorithm proposed by Australian scholars Mirjalili and Lewis, which simulates the whale's unique bubble-net foraging method. Whale optimization algorithm simulates the whale's bubble net foraging behavior, and divides the algorithm into three stages, namely, the siege stage, the bubble net attack, and the search for the predatory stage. The whale first gradually obtains information about its prey by searching for it, and then the whale keeps approaching its prey by surrounding it and spiraling close to it, eventually reaching the best solution to the problem.
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