112 lines
2.9 KiB
Python
112 lines
2.9 KiB
Python
# Copyright 2010 Hakan Kjellerstrand hakank@bonetmail.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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Subset sum problem in Google CP Solver.
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From Katta G. Murty: 'Optimization Models for Decision Making', page 340
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http://ioe.engin.umich.edu/people/fac/books/murty/opti_model/junior-7.pdf
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'''
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Example 7.8.1
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A bank van had several bags of coins, each containing either
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16, 17, 23, 24, 39, or 40 coins. While the van was parked on the
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street, thieves stole some bags. A total of 100 coins were lost.
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It is required to find how many bags were stolen.
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'''
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Compare with the following models:
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* Comet: http://www.hakank.org/comet/subset_sum.co
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* ECLiPSE: http://www.hakank.org/eclipse/subset_sum.ecl
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* Gecode: http://www.hakank.org/gecode/subset_sum.cpp
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* MiniZinc: http://www.hakank.org/minizinc/subset_sum.mzn
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* Tailor/Essence': http://www.hakank.org/tailor/subset_sum.py
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* SICStus: http://hakank.org/sicstus/subset_sum.pl
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This model was created by Hakan Kjellerstrand (hakank@bonetmail.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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import string
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import sys
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from ortools.constraint_solver import pywrapcp
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def subset_sum(solver, values, total):
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n = len(values)
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x = [solver.IntVar(0, n) for i in range(n)]
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ss = solver.IntVar(0, n)
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solver.Add(ss == solver.Sum(x))
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solver.Add(total == solver.ScalProd(x, values))
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return x, ss
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def main(coins, total):
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# Create the solver.
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solver = pywrapcp.Solver("n-queens")
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#
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# data
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#
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print "coins:", coins
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print "total:", total
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print
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#
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# declare variables
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#
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#
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# constraints
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#
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x, ss = subset_sum(solver, coins, total)
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#
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# solution and search
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#
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solution = solver.Assignment()
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solution.Add(x)
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solution.Add(ss)
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# db: DecisionBuilder
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db = solver.Phase(x,
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solver.CHOOSE_FIRST_UNBOUND,
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solver.ASSIGN_MIN_VALUE)
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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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print "ss:", ss.Value()
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print "x: ", [x[i].Value() for i in range(len(x))]
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print
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num_solutions += 1
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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()
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coins = [16, 17, 23, 24, 39, 40]
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total = 100
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if __name__ == "__main__":
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if len(sys.argv) > 1:
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total = string.atoi(sys.argv[1])
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main(coins, total)
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