我想到解决约束的优化问题。
max{ln(c1)+ln(c2)}
s.t. 4(c1)+6(c2)≤40
我写了这个代号:
import numpy as np
from scipy import optimize
def main():
"""
solving a regular constrained optimization problem
max ln(cons[0]) + ln(cons[1])
st. prices[0]*cons[0] + prices[1]*cons[1] <= I
"""
prices = np.array([4.0, 6.0])
I = 40.0
util = lambda cons: np.dot( np.log(cons)) #define utility function
budget = lambda cons: I - np.dot(prices, cons) #define the budget constraint
initval = 40.0*np.ones(2) #set the initial guess for the algorithm
res = optimize.minimize(lambda x: -util(x), initval, method='slsqp',
constraints={'type':'ineq', 'fun':budget},
tol=1e-9)
assert res['success'] == True
print(res)
不幸的是,我的代码不打印的任何解决方案。 你可以帮我找出为什么?