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basic_example.py
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basic_example.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.
"""Minimal example to call the GLOP solver."""
# [START program]
# [START import]
from ortools.linear_solver import pywraplp
from ortools.init import pywrapinit
# [END import]
def main():
# [START solver]
# Create the linear solver with the GLOP backend.
solver = pywraplp.Solver.CreateSolver('GLOP')
if not solver:
return
# [END solver]
# [START variables]
# Create the variables x and y.
x = solver.NumVar(0, 1, 'x')
y = solver.NumVar(0, 2, 'y')
print('Number of variables =', solver.NumVariables())
# [END variables]
# [START constraints]
# Create a linear constraint, 0 <= x + y <= 2.
ct = solver.Constraint(0, 2, 'ct')
ct.SetCoefficient(x, 1)
ct.SetCoefficient(y, 1)
print('Number of constraints =', solver.NumConstraints())
# [END constraints]
# [START objective]
# Create the objective function, 3 * x + y.
objective = solver.Objective()
objective.SetCoefficient(x, 3)
objective.SetCoefficient(y, 1)
objective.SetMaximization()
# [END objective]
# [START solve]
solver.Solve()
# [END solve]
# [START print_solution]
print('Solution:')
print('Objective value =', objective.Value())
print('x =', x.solution_value())
print('y =', y.solution_value())
# [END print_solution]
if __name__ == '__main__':
pywrapinit.CppBridge.InitLogging('basic_example.py')
cpp_flags = pywrapinit.CppFlags()
cpp_flags.logtostderr = True
cpp_flags.log_prefix = False
pywrapinit.CppBridge.SetFlags(cpp_flags)
main()
# [END program]