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Copyright 2022 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.

simple_lp_program_mb¶

Run in Google Colab

View source on GitHub

First, you must install ortools package in this colab.

In [ ]:

!pip install ortools

Minimal example to call the GLOP solver using model_builder.

In [ ]:

import math

from ortools.model_builder.python import model_builder


def main():
    # Create the model.
    model = model_builder.ModelBuilder()

    # Create the variables x and y.
    x = model.new_num_var(0.0, math.inf, 'x')
    y = model.new_num_var(0.0, math.inf, 'y')

    print('Number of variables =', model.num_variables)

    # x + 7 * y <= 17.5.
    ct = model.add(x + 7 * y <= 17.5)

    # x <= 3.5.
    model.add(x <= 3.5)

    print('Number of constraints =', model.num_constraints)

    # Maximize x + 10 * y.
    model.maximize(x + 10 * y)

    # Create the solver with the GLOP backend, and solve the model.
    solver = model_builder.ModelSolver('glop')
    status = solver.solve(model)

    if status == model_builder.SolveStatus.OPTIMAL:
        print('Solution:')
        print('Objective value =', solver.objective_value)
        print('x =', solver.value(x))
        print('y =', solver.value(y))

        print('dual_value(ct) =', solver.dual_value(ct))
        print('reduced_cost(x) =', solver.reduced_cost(x))
    else:
        print('The problem does not have an optimal solution.')

    print('\nAdvanced usage:')
    print('Problem solved in %f seconds' % solver.wall_time)


main()