Example matrix1.py

This is the complete source code for our example (also available in <installdir>/examples/python/matrix1.py)...

#!/usr/bin/env python3.7

# Copyright 2021, Gurobi Optimization, LLC

# This example formulates and solves the following simple MIP model
# using the matrix API:
#  maximize
#        x +   y + 2 z
#  subject to
#        x + 2 y + 3 z <= 4
#        x +   y       >= 1
#        x, y, z binary

import gurobipy as gp
from gurobipy import GRB
import numpy as np
import scipy.sparse as sp


    # Create a new model
    m = gp.Model("matrix1")

    # Create variables
    x = m.addMVar(shape=3, vtype=GRB.BINARY, name="x")

    # Set objective
    obj = np.array([1.0, 1.0, 2.0])
    m.setObjective(obj @ x, GRB.MAXIMIZE)

    # Build (sparse) constraint matrix
    val = np.array([1.0, 2.0, 3.0, -1.0, -1.0])
    row = np.array([0, 0, 0, 1, 1])
    col = np.array([0, 1, 2, 0, 1])

    A = sp.csr_matrix((val, (row, col)), shape=(2, 3))

    # Build rhs vector
    rhs = np.array([4.0, -1.0])

    # Add constraints
    m.addConstr(A @ x <= rhs, name="c")

    # Optimize model

    print('Obj: %g' % m.objVal)

except gp.GurobiError as e:
    print('Error code ' + str(e.errno) + ": " + str(e))

except AttributeError:
    print('Encountered an attribute error')

You will need to have both the NumPy package and the SciPy sparse matrix package in your Python environment to run this example. The easiest ways to obtain a suitable Python environment is to install the Anaconda Python distribution, or to install these packages in your Python environment through python -m pip install numpy scipy.

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