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simple_mip_program_mb.py
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simple_mip_program_mb.py
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#!/usr/bin/env python3
# Copyright 2010-2022 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.
# [START program]
"""Integer programming examples that show how to use the APIs."""
# [START import]
import math
from ortools.linear_solver.python import model_builder
# [END import]
def main():
# [START model]
# Create the model.
model = model_builder.ModelBuilder()
# [END model]
# [START variables]
# x and y are integer non-negative variables.
x = model.new_int_var(0.0, math.inf, 'x')
y = model.new_int_var(0.0, math.inf, 'y')
print('Number of variables =', model.num_variables)
# [END variables]
# [START constraints]
# x + 7 * y <= 17.5.
model.add(x + 7 * y <= 17.5)
# x <= 3.5.
model.add(x <= 3.5)
print('Number of constraints =', model.num_constraints)
# [END constraints]
# [START objective]
# Maximize x + 10 * y.
model.maximize(x + 10 * y)
# [END objective]
# [START solve]
# Create the solver with the SCIP backend, and solve the model.
solver = model_builder.ModelSolver('scip')
status = solver.solve(model)
# [END solve]
# [START print_solution]
if status == model_builder.SolveStatus.OPTIMAL:
print('Solution:')
print('Objective value =', solver.objective_value)
print('x =', solver.value(x))
print('y =', solver.value(y))
else:
print('The problem does not have an optimal solution.')
# [END print_solution]
# [START advanced]
print('\nAdvanced usage:')
print('Problem solved in %f seconds' % solver.wall_time)
# [END advanced]
if __name__ == '__main__':
main()
# [END program]