scipy.optimize 求解非線性Rosenbrock最優化問題 python

利用python軟體程式設計求解非線性Rosenbrock最優化問題

m i n f ( x , y ) = ( 1 − x ) 2 + 100 ( y − x 2 ) 2 min f(x, y) = (1-x)^{2}+100(y-x^{2})^{2} minf(x,y)=(1−x)2+100(y−x2)2

− 2 ≤ x ≤ 2 -2\leq x \leq 2 −2≤x≤2

− 1 ≤ y ≤ 3 -1\leq y \leq 3 −1≤y≤3

程式，如下

from scipy.optimize import minimize
fun = lambda x: (1 - x[0]) ** 2 + 100 * (x[1] - x[0] ** 2) ** 2
bnds = ((-2, 2), (-1, 3))
res = minimize(fun, (2, 0), method='SLSQP', bounds=bnds)
print(res.x)
           

結果