93 lines
2.4 KiB
Python
93 lines
2.4 KiB
Python
# Copyright 2010 Hakan Kjellerstrand hakank@gmail.com
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#
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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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"""
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Scheduling speakers problem in Google CP Solver.
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From Rina Dechter, Constraint Processing, page 72
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Scheduling of 6 speakers in 6 slots.
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Compare with the following models:
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* MiniZinc: http://www.hakank.org/minizinc/scheduling_speakers.mzn
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* SICStus Prolog: http://www.hakank.org/sicstus/scheduling_speakers.pl
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* ECLiPSe: http://hakank.org/eclipse/scheduling_speakers.ecl
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* Gecode: http://hakank.org/gecode/scheduling_speakers.cpp
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This model was created by Hakan Kjellerstrand (hakank@gmail.com)
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Also see my other Google CP Solver models:
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http://www.hakank.org/google_or_tools/
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"""
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from __future__ import print_function
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from ortools.constraint_solver import pywrapcp
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def main():
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# Create the solver.
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solver = pywrapcp.Solver('Scheduling speakers')
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#
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# data
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#
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n = 6 # number of speakers
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# slots available to speak
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available = [
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# Reasoning:
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[3, 4, 5, 6], # 2) the only one with 6 after speaker F -> 1
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[3, 4], # 5) 3 or 4
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[2, 3, 4, 5], # 3) only with 5 after F -> 1 and A -> 6
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[2, 3, 4], # 4) only with 2 after C -> 5 and F -> 1
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[3, 4], # 5) 3 or 4
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[1, 2, 3, 4, 5, 6] # 1) the only with 1
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]
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#
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# variables
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#
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x = [solver.IntVar(1, n, 'x[%i]' % i) for i in range(n)]
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#
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# constraints
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#
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solver.Add(solver.AllDifferent(x))
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for i in range(n):
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solver.Add(solver.MemberCt(x[i], available[i]))
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#
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# search and result
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#
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db = solver.Phase(x, solver.INT_VAR_DEFAULT, solver.INT_VALUE_DEFAULT)
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solver.NewSearch(db)
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num_solutions = 0
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while solver.NextSolution():
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num_solutions += 1
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print('x:', [x[i].Value() for i in range(n)])
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solver.EndSearch()
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print()
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print('num_solutions:', num_solutions)
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print('failures:', solver.Failures())
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print('branches:', solver.Branches())
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print('WallTime:', solver.WallTime(), 'ms')
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if __name__ == '__main__':
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main()
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