How to use model.get(A) function?
OngoingI want to solve an LPP with GUROBI OPTIMIZATION. I want the coefficient matrix of the constraints in a CSV file. I read that model.get(A) function works. But I am unable to use this function.
Could you please give an example to use model.get(A) function?

You can see a simple example of the getA method in the respective documentation. Once, you have the A matrix, you can then automatically convert the sparse matrix format to a dense one and write it to a CSV file. You could use the todense method of the scipy module.
import gurobipy as gp
import scipy as sp
import pandas as pd
m = gp.Model("mip1")
x = m.addVar(ub=2, name="x")
y = m.addVar(ub=2, name="y")
z = m.addVar(ub=1, name="z")
m.setObjective(x + y  z, GRB.MINIMIZE)
m.addConstr(x + 2 * y + 3 * z <= 4, "c0")
m.addConstr(x + y >= 1, "c1")
m.update()
A = m.getA()
denseMatrix = pd.DataFrame(data=sp.sparse.csr_matrix.todense(A))
denseMatrix.to_csv("Amatrix.csv", index=False)Best regards,
Jaromił0 
Thank you so much for your reply.
It really helps me a lot.
0 
Is it possible to use model.get A function with pyomo optimization?
How can we use this function?
Could you please give an example of this?
0 
Pyomo doesn't support all of the features available in the native Gurobi Python API. However, if you're using the "persistent" Gurobi interface, you can access the underlying \(\texttt{gurobipy}\) Model object using the \(\texttt{_solver_model}\) attribute of your GurobiPersistent object. You can use this object to call \(\texttt{gurobipy}\) methods like Model.getA(). For example:
model = ConcreteModel()
model.y = Var([1, 2], domain=NonNegativeReals)
model.my_constraint1 = Constraint(expr=3 * model.y[1] + 4 * model.y[2] <= 12)
model.my_constraint2 = Constraint(expr=5 * model.y[1] + model.y[2] <= 11)
solver = SolverFactory("gurobi_persistent", model=model)
A = solver._solver_model.getA()0 
I am using GUROBI OPTIMIZATION to solve an LPP with an MPS file format. I am modifying matrix A and I can get matrix A using getA function. Can I extract the cost vector (objective function coefficients) and the RHS vector (the b vector) from an MPS file? I want to solve the LPP by modifying A, the vector b, and the cost coefficient c.
Is it possible to get the b and c vectors from the MPS file?
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