Whale Optimization Algorithm python
- simple WOA (Whale Optimization Algorithm) implementation
- used Numpy for matrix computation (No For Loop)
- Original Paper here
- 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)
- 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)
- matplotlib==3.5.1
- numpy==1.20.0
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent