作业5.7

5.7

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from scipy.optimize import minimize, NonlinearConstraint
import numpy as np
 
if __name__=="__main__":
    fun=lambda x:np.sum(50*x+0.2*x**2)+4*(2*x[0]+x[1]-140)
    con_fun1 = lambda x:x[0]+x[1]+x[2]
    con_fun2 = lambda x:x[0]+x[1]
    con1 = NonlinearConstraint(con_fun1, 180, 180)
    con2 = NonlinearConstraint(con_fun2, 100, np.inf)
    cons = [con1,con2]
    lb = np.array([40,0,0])
    ub=np.array([100]*3)
    bound=np.vstack((lb,ub)).T 
    res=minimize(fun, np.zeros(3), method='SLSQP', bounds=bound, constraints=cons)
 
    print("最优解", np.round(res.x)) 
    print("最优值", fun(np.round(res.x)))
print("3010")