MVars and MConstrs in feasRelax

回答済み

Jonathan Baker

2023年08月30日 03:35

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• 
• 

Using the Python API, I would like to use feasRelax on a model using MVars and MConstrs. Following the examples I've seen for Vars and Constrs, here's the type of thing I've been trying.

import gurobipy as gp
from gurobipy import GRB

import numpy as np

m = gp.Model()

x = m.addMVar( 2 )
m.setObjective( x.sum() )

# Set infeasible constraints
A = np.array([
    [ 1  ,-1],
    [-1  ,-1],
    [-0.5, 1]
])
b = np.array([-1,-2,1.5])
c = m.addMConstr( A , x , '>=' , b )

m.feasRelax(
    0,
    False,
    None,
    None,
    None,
    [c],
    [1]
)

m.optimize()
print('Optimization status:',m.Status)
print(x.X)

The result in this case is

AttributeError: 'gurobipy.MConstr' object has no attribute '__cindex__'

I've tried quite a few variations, but I'm stumped. I'd rather not have to surrender and set up the slack variables myself ;-)

Thanks for any help!

関連

• FeasRelax

0

• 

  Riley Clement

  • Gurobi Staff

  2023年08月30日 04:59 編集済み

  Hi Jonathan,

  You can get your code to work using

  m.feasRelax(
      0,
      False,
      None,
      None,
      None,
      c.tolist(),
      [1]*c.size,
  )

  It may alternatively be worth using feasRelaxS too, which avoids the requirement of specifying which constraints to relax.

  - Riley

  1
• 

  Jonathan Baker

  2023年08月30日 17:04

  • 
  • 
  • 

  Ah, thanks so much! I had tried "list(c)" but I guess tolist() does something fancier.

  My actual application is more complicated that this example, and I need to specify the relaxable constraints. feasRelax will be much better than feasRelaxS for me.

  0

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