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# Copyright 2010 Hakan Kjellerstrand hakank@gmail.com
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
n-queens problem in Google CP Solver.
N queens problem.
This version use NewSearch()/NextSolution() for looping through
the solutions.
This model was created by Hakan Kjellerstrand (hakank@gmail.com)
Also see my other Google CP Solver models: http://www.hakank.org/google_or_tools/
"""
import sys, string
from constraint_solver import pywrapcp
def main(n=8, num_sol=0, print_sol=1):
# Create the solver.
solver = pywrapcp.Solver('n-queens')
#
# data
#
# n = 8 # size of board (n x n)
print "n:", n
print "num_sol:", num_sol
print "print_sol:", print_sol
# declare variables
q = [solver.IntVar(0,n-1, 'x%i' % i) for i in range(n)]
#
# constraints
#
solver.Add(solver.AllDifferent(q,True))
for i in range(n):
for j in range(i):
solver.Add(q[i] != q[j])
solver.Add(q[i] + i != q[j] + j)
solver.Add(q[i] - i != q[j] - j)
# for i in range(n):
# for j in range(i):
# solver.Add(abs(q[i]-q[j]) != abs(i-j))
# symmetry breaking
# solver.Add(q[0] == 0)
#
# solution and search
#
solution = solver.Assignment()
solution.Add([q[i] for i in range(n)])
# db: DecisionBuilder
# db = solver.Phase([q[i] for i in range(n)],
# #solver.CHOOSE_FIRST_UNBOUND,
# solver.CHOOSE_MIN_SIZE_LOWEST_MAX,
# solver.ASSIGN_CENTER_VALUE)
parameters = pywrapcp.DefaultPhaseParameters()
# parameters.heuristic_num_failures_limit = 1000
parameters.heuristic_period = n*n*n
# parameters.var_selection_schema = parameters.CHOOSE_MAX_SUM_IMPACT
parameters.var_selection_schema = parameters.CHOOSE_MAX_AVERAGE_IMPACT
# parameters.var_selection_schema = parameters.CHOOSE_MAX_VALUE_IMPACT
# parameters.value_selection_schema = parameters.SELECT_MIN_IMPACT
# parameters.value_selection_schema = parameters.SELECT_MAX_IMPACT
# parameters.initialization_splits = 10
# parameters.initialization_splits = 20
# parameters.random_seed = 0
db = solver.DefaultPhase(q, parameters)
solver.NewSearch(db)
num_solutions = 0
while solver.NextSolution():
if print_sol:
qval = [q[i].Value() for i in range(n)]
print "q:", qval
for i in range(n):
for j in range(n):
if qval[i] == j:
print "Q",
else:
print "_",
print
print
num_solutions += 1
if num_sol > 0 and num_solutions >= num_sol:
break
solver.EndSearch()
print
print "num_solutions:", num_solutions
print "failures:", solver.failures()
print "branches:", solver.branches()
print "wall_time:", solver.wall_time()
n = 8
num_sol = 0
print_sol = 1
if __name__ == '__main__':
if len(sys.argv) > 1:
n = int(sys.argv[1])
if len(sys.argv) > 2:
num_sol = int(sys.argv[2])
if len(sys.argv) > 3:
print_sol = int(sys.argv[3])
main(n, num_sol, print_sol)
# print_sol = False
# show_all = False
# for n in range(1000,1001):
# print
# main(n, num_sol, print_sol)