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Intelligent optimization algorithm | Matlab implements Whale Optimization Algorithm (complete source code included)
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Step 1: Set the number of whales N and the maximum number of iterations of the algorithm tmax, and initialize the position information;
Step 2: Calculate the fitness of each whale, find the current optimal whale position and retain it;
Step 3: Calculate parameters a, p and coefficients Vectors A, C. Determine whether the probability p is less than 50%, if so, go directly to step 4, otherwise use the bubble net predator mechanism: perform position update according to formula (2-1); Step 4: Determine whether the absolute value of the coefficient vector A is less than 1, if
so Surround the prey: update the position according to formula (1-2); otherwise search for prey globally randomly: update the position according to formula (3-1);
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