# Copyright 2010-2018 Google LLC
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Integer programming examples that show how to use the APIs."""
# [START program]
# [START import]
from __future__ import print_function
from ortools.linear_solver import pywraplp
# [END import]


def main():
    # [START solver]
    # Create the mip solver with the CBC backend.
    solver = pywraplp.Solver('simple_mip_program',
                             pywraplp.Solver.CBC_MIXED_INTEGER_PROGRAMMING)
    # [END solver]

    # [START variables]
    infinity = solver.infinity()
    # x and y are integer non-negative variables.
    x = solver.IntVar(0.0, infinity, 'x')
    y = solver.IntVar(0.0, infinity, 'y')

    print('Number of variables =', solver.NumVariables())
    # [END variables]

    # [START constraints]
    # x + 7 * y <= 17.5.
    solver.Add(x + 7 * y <= 17.5)

    # x <= 3.5.
    solver.Add(x <= 3.5)

    print('Number of constraints =', solver.NumConstraints())
    # [END constraints]

    # [START objective]
    # Maximize x + 10 * y.
    solver.Maximize(x + 10 * y)
    # [END objective]

    # [START solve]
    result_status = solver.Solve()
    # The problem has an optimal solution.
    assert result_status == pywraplp.Solver.OPTIMAL

    # The solution looks legit (when using solvers others than
    # GLOP_LINEAR_PROGRAMMING, verifying the solution is highly recommended!).
    assert solver.VerifySolution(1e-7, True)
    # [END solve]

    # [START print_solution]
    print('Solution:')
    print('Objective value =', solver.Objective().Value())
    print('x =', x.solution_value())
    print('y =', y.solution_value())
    # [END print_solution]

    # [START advanced]
    print('\nAdvanced usage:')
    print('Problem solved in %f milliseconds' % solver.wall_time())
    print('Problem solved in %d iterations' % solver.iterations())
    print('Problem solved in %d branch-and-bound nodes' % solver.nodes())
    # [END advanced]


if __name__ == '__main__':
    main()
# [END program]