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Whale Optimization Algorithm python

  • simple WOA (Whale Optimization Algorithm) implementation
  • used Numpy for matrix computation (No For Loop)
  • Original Paper here

Test

  • Rosenbrock function (=Banana function)
    • minimum solution : (1, 1)
def f(X):
    a, b = 1, 100
    sol = []
    for x in X:
        sol.append(((a - x[0]) ** 2) + b*(x[1]-x[0]**2)**2)
    return np.array(sol)
  • Rastrigin function
    • minimum solution : (0, 0)
def f(X):
    A = 10
    sol = []
    for ind in X:
        sol.append(A*len(ind) + sum([(i**2 - A * np.cos(2 * np.pi * i)) for i in ind]) )
    return np.array(sol)

WOA

  • Whale Optimization Algorithm Code in woa.py
    • # of whales : n_whale (default: 100, init parameter)
    • # of iterations : n_iter (default: 100, init parameter)
    • Spiral Constant : spiral_constant (default: 0.5, init parameter)
      • controls the shape of the spiral which whales follow (from here)

Requirements

  • matplotlib==3.5.1
  • numpy==1.20.0