[최적화] Google OR-Tools Linear Optimization (4)The N-queens Problem
in Data on Optimization
Google OR-Tools Linear Optimization (4)The N-queens Problem 에 대한 간단한 정리
N-Queens 문제
- 어떤 퀸이 NxN 체스판에 배치되어 두 사람이 서로 공격하지 않도록 할 수 있나요?(가로, 세로, 대각 공격)
파이썬 코드
솔루션 찾기
"""OR-Tools solution to the N-queens problem."""
import sys
import time
from ortools.sat.python import cp_model
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 solution_count(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):
# 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 rows must be different.
model.AddAllDifferent(queens)
# All columns must be different because the indices of queens are all
# different.
# No two queens can be on the same diagonal.
model.AddAllDifferent(queens[i] + i for i in range(board_size))
model.AddAllDifferent(queens[i] - i for i in range(board_size))
# Solve the model.
solver = cp_model.CpSolver()
solution_printer = NQueenSolutionPrinter(queens)
solver.parameters.enumerate_all_solutions = True
solver.Solve(model, solution_printer)
# Statistics.
print('\nStatistics')
print(f' conflicts : {solver.NumConflicts()}')
print(f' branches : {solver.NumBranches()}')
print(f' wall time : {solver.WallTime()} s')
print(f' solutions found: {solution_printer.solution_count()}')
if __name__ == '__main__':
# By default, solve the 8x8 problem.
size = 4
main(size)
결과값
Solution 0, time = 0.011988 s
_ _ Q _
Q _ _ _
_ _ _ Q
_ Q _ _
Solution 1, time = 0.013119 s
_ Q _ _
_ _ _ Q
Q _ _ _
_ _ Q _
Statistics
conflicts : 0
branches : 17
wall time : 0.013535707000000001 s
solutions found: 2
참고 : https://developers.google.com/optimization/cp/queens