How to get value from decision matrix after optimization?

Answered

Ilya Tuzhilin

February 14, 2023 13:50

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Suppose I have a matrix defined as follows:

 

MM = model.addVars(I, J, vtype=GRB.BINARY, name='MM')

...

model.optimize()

After Solution was found I want to save matrix MM as a 2D numpy array Result to use later in the code. Smth like: Result = [[1, 0, 0], [0, 1, 0], [0,1,0]] (where MM[1][1]=1 for example)

How can I do this in python?

Related to

• Formulation
• Python

0

• 

  Jaromił Najman

  • Gurobi Staff

  February 14, 2023 18:04

  You can get the optimal solution value by accessing the X attribute of a given variable.

  The following code snippet shows an example of how to construct such a numpy array. Please note that it is probably not the most Pythonic way to achieve it. Maybe someone could provide a more Pythonic way.

  import gurobipy as gp
  from gurobipy import GRB
  import numpy as np
  
  m = gp.Model()
  
  I = 3
  J = 2
  
  MM = m.addVars(I,J,vtype=GRB.BINARY, name="MM")
  
  m.addConstr(MM[1,1] == 1)
  m.setObjective(gp.quicksum(MM))
  m.optimize()
  
  array = np.array(0)
  if m.SolCount > 0:
      # get tupledict holding solution values
      L = []
      for i in range(I):
          K = []
          for j in range(J):
              K.append(MM[i,j].X)
  
          L.append(K)
      
      array = np.array(L)
  
  print(array)

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