77 lines
2.2 KiB
Python
77 lines
2.2 KiB
Python
# Copyright 2010-2017 Google
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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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"""Link integer constraints together."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from ortools.sat.python import cp_model
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class VarArraySolutionPrinter(cp_model.CpSolverSolutionCallback):
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"""Print intermediate solutions."""
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def __init__(self, variables):
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cp_model.CpSolverSolutionCallback.__init__(self)
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self.__variables = variables
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self.__solution_count = 0
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def OnSolutionCallback(self):
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self.__solution_count += 1
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for v in self.__variables:
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print('%s=%i' % (v, self.Value(v)), end=' ')
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print()
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def SolutionCount(self):
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return self.__solution_count
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def ChannelingSample():
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"""Demonstrates how to link integer constraints together."""
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# Model.
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model = cp_model.CpModel()
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# Variables.
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x = model.NewIntVar(0, 10, 'x')
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y = model.NewIntVar(0, 10, 'y')
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b = model.NewBoolVar('b')
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# Implement b == (x >= 5).
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model.Add(x >= 5).OnlyEnforceIf(b)
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model.Add(x < 5).OnlyEnforceIf(b.Not())
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# b implies (y == 10 - x).
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model.Add(y == 10 - x).OnlyEnforceIf(b)
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# not(b) implies y == 0.
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model.Add(y == 0).OnlyEnforceIf(b.Not())
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# Search for x values in increasing order.
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model.AddDecisionStrategy([x], cp_model.CHOOSE_FIRST,
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cp_model.SELECT_MIN_VALUE)
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# Create a solver and solve with a fixed search.
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solver = cp_model.CpSolver()
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# Force solver to follow the decision strategy exactly.
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solver.parameters.search_branching = cp_model.FIXED_SEARCH
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# Searches and prints out all solutions.
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solution_printer = VarArraySolutionPrinter([x, y, b])
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solver.SearchForAllSolutions(model, solution_printer)
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ChannelingSample()
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