My LP model does not give expected answer

回答済み

Geesara Kulathunga

2020年12月01日 09:03 編集済み

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import gurobipy as gp
from scipy.optimize import linprog
import numpy as np

lp_m = gp.Model()
w = np.array([1., 5., 1.])
halfspaces = np.array([
[1.*w[0], 1.*w[1], 1.*w[2], -10 ],
[ 1., 0., 0., -4],
[ 0., 1., 0., -4],
[ 0., 0., 1., -4],
[-1., 0., 0., 0],
[ 0., -1., 0., 0],
[ 0., 0., -1., 0]
])

A = halfspaces[:,0:3]
b = -1*halfspaces[:,-1]
cost = np.zeros(A.shape[1])
opt_x = lp_m.addMVar((A.shape[1],), name="x")
lp_m.setObjective(cost@opt_x)
lp_m.addConstr(A@opt_x <= b)
lp_m.optimize()
print(opt_x.X) #  [0. 0. 0.]

res = linprog(c=cost, A_ub=A, b_ub=b, method='interior-point')
print(res.x) # [1.65708642 1.040279 1.65708642]

I want to use gurobi instead of scipy, but I am not getting the same answer which I get in scipy, Could someone help me what went wrong here?

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• 正式なコメント

  

  Simranjit Kaur

  • Gurobi Staff

  2025年06月23日 03:04 編集済み

  This post is more than three years old. Some information may not be up to date. For current information, please check the Gurobi Documentation or Knowledge Base. If you need more help, please create a new post in the community forum. Or why not try our AI Gurobot?.
• 

  Jaromił Najman

  • Gurobi Staff

  2020年12月04日 12:10

  This is a cross-post to stackoverflow - LP model does not give expected answer.

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