Simple ortools example for solving constraint optimization with CP solver

ortools_example.py

from ortools.sat.python import cp_model

# setup a model which represents the constraint optimization problem
model = cp_model.CpModel()
# declare variables
# x and y are two integer with range of 0 to 2
x = model.NewIntVar(0, 2, 'x')
y = model.NewIntVar(0, 2, 'y')
# add constraint: x+y <= 1
model.Add(x + y <= 1)
# setup the objective function
obj = 2*x + y
model.Maximize(obj)

# solve the optimization problem
solver = cp_model.CpSolver()
status = solver.Solve(model)

if solver.StatusName(status) == 'OPTIMAL':
    print('x:', solver.Value(x))
    print('y:', solver.Value(y))
else:
    print('no optimal solution')