let us consider following code :

from scipy.optimize import minimize

def  obj(x):
    x1 =x[0]
    x2 =x[1]
    x3 =x[2]
    return (x1*1000+x2*1000+x3*500)

def constr(x):
    x1 = x[0]
    x2 = x[1]
    x3 = x[2]
    return 150-(x1+x2+x3)

bound_x1 =(0,None)
bound_x2 =(0,None)
bound_x3 =(0,None)
const_form ={"type":"ineq","fun":constr}
x0 =[0,0,0]
result =minimize(obj,x0,method ='SLSQP',constraints=const_form,bounds=[bound_x1,bound_x2,bound_x3])
print(result['x'])
print(result)

this problem is taken from the following site :Optimization

i want to maximize, if i run this program , result is :

minimization works pretty fine, but i want maximization, based on a little research, i have updated code like this :

def  obj(x,sign=-1.0):
    x1 =x[0]
    x2 =x[1]
    x3 =x[2]
    return (x1*1000+x2*1000+x3*500)*sign

and got following output :

based on website, the answer should be :

is there anything missed in my code?