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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 2020, 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 numpy as np import scipy.sparse as sp import gurobipy as gp from gurobipy import GRB try: # 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 data = 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((data, (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 m.optimize() print(x.X) 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 way to obtain a suitable Python environment is to install the Anaconda Python distribution.