175 lines
4.3 KiB
Python
175 lines
4.3 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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Set partition problem in Google CP Solver.
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Problem formulation from
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http://www.koalog.com/resources/samples/PartitionProblem.java.html
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'''
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This is a partition problem.
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Given the set S = {1, 2, ..., n},
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it consists in finding two sets A and B such that:
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A U B = S,
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|A| = |B|,
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sum(A) = sum(B),
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sum_squares(A) = sum_squares(B)
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'''
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This model uses a binary matrix to represent the sets.
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Also, compare with other models which uses var sets:
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* MiniZinc: http://www.hakank.org/minizinc/set_partition.mzn
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* Gecode/R: http://www.hakank.org/gecode_r/set_partition.rb
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* Comet: http://hakank.org/comet/set_partition.co
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* Gecode: http://hakank.org/gecode/set_partition.cpp
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* ECLiPSe: http://hakank.org/eclipse/set_partition.ecl
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* SICStus: http://hakank.org/sicstus/set_partition.pl
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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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import sys
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from ortools.constraint_solver import pywrapcp
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#
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# Partition the sets (binary matrix representation).
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#
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def partition_sets(x, num_sets, n):
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solver = list(x.values())[0].solver()
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for i in range(num_sets):
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for j in range(num_sets):
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if i != j:
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b = solver.Sum([x[i, k] * x[j, k] for k in range(n)])
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solver.Add(b == 0)
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# ensure that all integers is in
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# (exactly) one partition
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b = [x[i, j] for i in range(num_sets) for j in range(n)]
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solver.Add(solver.Sum(b) == n)
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def main(n=16, num_sets=2):
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# Create the solver.
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solver = pywrapcp.Solver("Set partition")
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#
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# data
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#
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print("n:", n)
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print("num_sets:", num_sets)
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print()
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# Check sizes
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assert n % num_sets == 0, "Equal sets is not possible."
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#
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# variables
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#
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# the set
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a = {}
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for i in range(num_sets):
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for j in range(n):
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a[i, j] = solver.IntVar(0, 1, "a[%i,%i]" % (i, j))
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a_flat = [a[i, j] for i in range(num_sets) for j in range(n)]
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#
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# constraints
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#
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# partition set
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partition_sets(a, num_sets, n)
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for i in range(num_sets):
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for j in range(i, num_sets):
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# same cardinality
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solver.Add(
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solver.Sum([a[i, k] for k in range(n)]) == solver.Sum(
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[a[j, k] for k in range(n)]))
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# same sum
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solver.Add(
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solver.Sum([k * a[i, k] for k in range(n)]) == solver.Sum(
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[k * a[j, k] for k in range(n)]))
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# same sum squared
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solver.Add(
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solver.Sum([(k * a[i, k]) * (k * a[i, k]) for k in range(n)]) ==
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solver.Sum([(k * a[j, k]) * (k * a[j, k]) for k in range(n)]))
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# symmetry breaking for num_sets == 2
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if num_sets == 2:
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solver.Add(a[0, 0] == 1)
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#
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# search and result
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#
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db = solver.Phase(a_flat, 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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a_val = {}
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for i in range(num_sets):
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for j in range(n):
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a_val[i, j] = a[i, j].Value()
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sq = sum([(j + 1) * a_val[0, j] for j in range(n)])
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print("sums:", sq)
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sq2 = sum([((j + 1) * a_val[0, j])**2 for j in range(n)])
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print("sums squared:", sq2)
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for i in range(num_sets):
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if sum([a_val[i, j] for j in range(n)]):
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print(i + 1, ":", end=" ")
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for j in range(n):
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if a_val[i, j] == 1:
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print(j + 1, end=" ")
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print()
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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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n = 16
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num_sets = 2
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if __name__ == "__main__":
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if len(sys.argv) > 1:
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n = int(sys.argv[1])
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if len(sys.argv) > 2:
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num_sets = int(sys.argv[2])
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main(n, num_sets)
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