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mip1.py
#!/usr/bin/env python3.7 # Copyright 2023, Gurobi Optimization, LLC # This example formulates and solves the following simple MIP model: # 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 try: # Create a new model m = gp.Model("mip1") # Create variables x = m.addVar(vtype=GRB.BINARY, name="x") y = m.addVar(vtype=GRB.BINARY, name="y") z = m.addVar(vtype=GRB.BINARY, name="z") # Set objective m.setObjective(x + y + 2 * z, GRB.MAXIMIZE) # Add constraint: x + 2 y + 3 z <= 4 m.addConstr(x + 2 * y + 3 * z <= 4, "c0") # Add constraint: x + y >= 1 m.addConstr(x + y >= 1, "c1") # Optimize model m.optimize() for v in m.getVars(): print('%s %g' % (v.VarName, v.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')