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ortools-clone/examples/python/nqueens_sat.py

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3.2 KiB
Python

#!/usr/bin/env python3
# Copyright 2010-2022 Google LLC
# 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.
"""CP/SAT model for the N-queens problem."""
import time
from absl import app
from absl import flags
from ortools.sat.python import cp_model
_SIZE = flags.DEFINE_integer('size', 8, 'Number of queens.')
class NQueenSolutionPrinter(cp_model.CpSolverSolutionCallback):
"""Print intermediate solutions."""
def __init__(self, queens):
cp_model.CpSolverSolutionCallback.__init__(self)
self.__queens = queens
self.__solution_count = 0
self.__start_time = time.time()
def SolutionCount(self):
return self.__solution_count
def on_solution_callback(self):
current_time = time.time()
print('Solution %i, time = %f s' %
(self.__solution_count, current_time - self.__start_time))
self.__solution_count += 1
all_queens = range(len(self.__queens))
for i in all_queens:
for j in all_queens:
if self.Value(self.__queens[j]) == i:
# There is a queen in column j, row i.
print('Q', end=' ')
else:
print('_', end=' ')
print()
print()
def main(_):
board_size = _SIZE.value
### Creates the solver.
model = cp_model.CpModel()
### Creates the variables.
# The array index is the column, and the value is the row.
queens = [
model.NewIntVar(0, board_size - 1, 'x%i' % i) for i in range(board_size)
]
### Creates the constraints.
# All columns must be different because the indices of queens are all
# different, so we just add the all different constraint on the rows.
model.AddAllDifferent(queens)
# No two queens can be on the same diagonal.
diag1 = []
diag2 = []
for i in range(board_size):
q1 = model.NewIntVar(0, 2 * board_size, 'diag1_%i' % i)
q2 = model.NewIntVar(-board_size, board_size, 'diag2_%i' % i)
diag1.append(q1)
diag2.append(q2)
model.Add(q1 == queens[i] + i)
model.Add(q2 == queens[i] - i)
model.AddAllDifferent(diag1)
model.AddAllDifferent(diag2)
### Solve model.
solver = cp_model.CpSolver()
solution_printer = NQueenSolutionPrinter(queens)
# Enumerate all solutions.
solver.parameters.enumerate_all_solutions = True
# Solve.
solver.Solve(model, solution_printer)
print()
print('Statistics')
print(' - conflicts : %i' % solver.NumConflicts())
print(' - branches : %i' % solver.NumBranches())
print(' - wall time : %f s' % solver.WallTime())
print(' - solutions found : %i' % solution_printer.SolutionCount())
if __name__ == '__main__':
app.run(main)