81 lines
3.0 KiB
Python
81 lines
3.0 KiB
Python
#!/usr/bin/env python3
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# Copyright 2023 RTE
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""MIP example/test that shows how to use the callback API."""
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from ortools.linear_solver import pywraplp
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from ortools.linear_solver.pywraplp import MPCallbackContext, MPCallback
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import random
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import unittest
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class MyMPCallback(MPCallback):
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def __init__(self, mp_solver: pywraplp.Solver):
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super().__init__(False, False)
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self._mp_solver_ = mp_solver
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self._solutions_ = 0
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self._last_var_values_ = [0] * len(mp_solver.variables())
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def RunCallback(self, ctx: MPCallbackContext):
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self._solutions_ += 1
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for i in range(0, len(self._mp_solver_.variables())) :
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self._last_var_values_[i] = ctx.VariableValue(self._mp_solver_.variable(i))
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class TestSiriusXpress(unittest.TestCase):
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def test_callback(self):
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"""Builds a large MIP that is difficult to solve, in order for us to have time to intercept non-optimal
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feasible solutions using callback"""
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solver = pywraplp.Solver.CreateSolver('XPRESS_MIXED_INTEGER_PROGRAMMING')
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n_vars = 30
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max_time = 30
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if not solver:
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return
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random.seed(123)
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objective = solver.Objective()
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objective.SetMaximization()
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for i in range(0, n_vars):
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x = solver.IntVar(-random.random() * 200, random.random() * 200, 'x_' + str(i))
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objective.SetCoefficient(x, random.random() * 200 - 100)
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if i == 0:
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continue
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rand1 = -random.random() * 2000
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rand2 = random.random() * 2000
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c = solver.Constraint(min(rand1, rand2), max(rand1, rand2))
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c.SetCoefficient(x, random.random() * 200 - 100)
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for j in range(0, i):
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c.SetCoefficient(solver.variable(j), random.random() * 200 - 100)
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solver.SetSolverSpecificParametersAsString("PRESOLVE 0 MAXTIME " + str(max_time))
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solver.EnableOutput()
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cb = MyMPCallback(solver)
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solver.SetCallback(cb)
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solver.Solve()
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# This is a tough MIP, in 30 seconds XPRESS should have found at least 5
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# solutions (tested with XPRESS v9.0, may change in later versions)
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self.assertTrue(cb._solutions_ > 5)
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# Test that the last solution intercepted by callback is the same as the optimal one retained
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for i in range(0, len(solver.variables())):
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self.assertAlmostEqual(cb._last_var_values_[i], solver.variable(i).SolutionValue())
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if __name__ == '__main__':
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unittest.main()
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