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ortools-clone/examples/python/integer_programming.py

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#!/usr/bin/env python3
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# Copyright 2010-2021 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."""
from ortools.linear_solver import pywraplp
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from ortools.init import pywrapinit
def Announce(solver, api_type):
print('---- Integer programming example with ' + solver + ' (' + api_type +
') -----')
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def RunIntegerExampleNaturalLanguageAPI(optimization_problem_type):
"""Example of simple integer program with natural language API."""
solver = pywraplp.Solver.CreateSolver(optimization_problem_type)
if not solver:
return
Announce(optimization_problem_type, 'natural language API')
infinity = solver.infinity()
# x1 and x2 are integer non-negative variables.
x1 = solver.IntVar(0.0, infinity, 'x1')
x2 = solver.IntVar(0.0, infinity, 'x2')
solver.Minimize(x1 + 2 * x2)
solver.Add(3 * x1 + 2 * x2 >= 17)
SolveAndPrint(solver, [x1, x2])
def RunIntegerExampleCppStyleAPI(optimization_problem_type):
"""Example of simple integer program with the C++ style API."""
solver = pywraplp.Solver.CreateSolver(optimization_problem_type)
if not solver:
return
Announce(optimization_problem_type, 'C++ style API')
infinity = solver.infinity()
# x1 and x2 are integer non-negative variables.
x1 = solver.IntVar(0.0, infinity, 'x1')
x2 = solver.IntVar(0.0, infinity, 'x2')
# Minimize x1 + 2 * x2.
objective = solver.Objective()
objective.SetCoefficient(x1, 1)
objective.SetCoefficient(x2, 2)
# 2 * x2 + 3 * x1 >= 17.
ct = solver.Constraint(17, infinity)
ct.SetCoefficient(x1, 3)
ct.SetCoefficient(x2, 2)
SolveAndPrint(solver, [x1, x2])
def SolveAndPrint(solver, variable_list):
"""Solve the problem and print the solution."""
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print('Number of variables = %d' % solver.NumVariables())
print('Number of constraints = %d' % solver.NumConstraints())
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)
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print('Problem solved in %f milliseconds' % solver.wall_time())
# The objective value of the solution.
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print('Optimal objective value = %f' % solver.Objective().Value())
# The value of each variable in the solution.
for variable in variable_list:
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print('%s = %f' % (variable.name(), variable.solution_value()))
print('Advanced usage:')
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print('Problem solved in %d branch-and-bound nodes' % solver.nodes())
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def RunAllIntegerExampleNaturalLanguageAPI():
RunIntegerExampleNaturalLanguageAPI('GLPK')
RunIntegerExampleNaturalLanguageAPI('CBC')
RunIntegerExampleNaturalLanguageAPI('SCIP')
RunIntegerExampleNaturalLanguageAPI('SAT')
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RunIntegerExampleNaturalLanguageAPI('Gurobi')
def RunAllIntegerExampleCppStyleAPI():
RunIntegerExampleCppStyleAPI('GLPK')
RunIntegerExampleCppStyleAPI('CBC')
RunIntegerExampleCppStyleAPI('SCIP')
RunIntegerExampleCppStyleAPI('SAT')
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RunIntegerExampleCppStyleAPI('Gurobi')
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def main():
RunAllIntegerExampleNaturalLanguageAPI()
RunAllIntegerExampleCppStyleAPI()
if __name__ == '__main__':
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pywrapinit.CppBridge.InitLogging('integer_programming.py')
cpp_flags = pywrapinit.CppFlags()
cpp_flags.logtostderr = True
cpp_flags.log_prefix = False
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pywrapinit.CppBridge.SetFlags(cpp_flags)
main()