Optimization with Python
Sample
import numpy as np
from scipy.optimize import minimize
# Define an objective function to minimize: f(x) = (x - 3)^2
def objective(x):
return (x[0] - 3) ** 2
# Initial guess and solve
result = minimize(objective, x0=[0.0])
print(f"Optimal x: {result.x[0]:.4f}") # Outputs close to 3.0000
Topics
- Choosing the Algorithm
- Specifying Options including max iterations
- Constraints
- Setting Initial Parmaters