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simulated-annealing.py
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simulated-annealing.py
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from datetime import datetime
import random
import math
class Board:
def __init__(self, queen_count=8):
self.queen_count = queen_count
self.reset()
def reset(self):
"""Reset the board with random queen positions."""
self.queens = [-1 for _ in range(self.queen_count)]
for i in range(self.queen_count):
self.queens[i] = random.randint(0, self.queen_count - 1)
def calculateCost(self):
"""Calculate the number of queen conflicts (threats) on the board."""
threat = 0
for queen in range(self.queen_count):
for next_queen in range(queen + 1, self.queen_count):
if self.queens[queen] == self.queens[next_queen] or abs(queen - next_queen) == abs(self.queens[queen] - self.queens[next_queen]):
threat += 1
return threat
@staticmethod
def calculateCostWithQueens(queens):
"""Calculate the number of conflicts (threats) given a set of queen positions."""
threat = 0
queen_count = len(queens)
for queen in range(queen_count):
for next_queen in range(queen + 1, queen_count):
if queens[queen] == queens[next_queen] or abs(queen - next_queen) == abs(queens[queen] - queens[next_queen]):
threat += 1
return threat
@staticmethod
def toString(queens):
"""Convert queen positions to a string representation with 0s and 1s."""
board_string = ""
for row, col in enumerate(queens):
for i in range(len(queens)):
if i == col:
board_string += "1"
else:
board_string += "0"
board_string += "\n"
return board_string
class SimulatedAnnealing:
def __init__(self, board):
self.elapsedTime = 0
self.board = board
self.temperature = 4.0 # Adjusted temperature value
self.sch = 0.99
self.startTime = datetime.now()
def run(self):
board = self.board
board_queens = self.board.queens[:]
solutionFound = False
# Simulated Annealing loop
for _ in range(170000):
# Update temperature
self.temperature *= self.sch
# Reset board to random state
board.reset()
successor_queens = board.queens[:]
# Calculate difference in cost between successor and current state
dw = Board.calculateCostWithQueens(successor_queens) - Board.calculateCostWithQueens(board_queens)
# Calculate acceptance probability
exp = math.exp(-dw * self.temperature)
# If better or accepted by probability, update current state
if dw > 0 or random.uniform(0, 1) < exp:
board_queens = successor_queens[:]
# If solution found, print and exit loop
if Board.calculateCostWithQueens(board_queens) == 0:
print("Solution:")
print(Board.toString(board_queens))
self.elapsedTime = self.getElapsedTime()
print("Success, Elapsed Time: %sms" % (str(self.elapsedTime)))
solutionFound = True
break
# If no solution found, print elapsed time
if not solutionFound:
self.elapsedTime = self.getElapsedTime()
print("Unsuccessful, Elapsed Time: %sms" % (str(self.elapsedTime)))
return self.elapsedTime
def getElapsedTime(self):
endTime = datetime.now()
elapsedTime = (endTime - self.startTime).microseconds / 1000
return elapsedTime
if __name__ == '__main__':
# Initialize board and print initial state
board = Board()
print("Board:")
print(Board.toString(board.queens))
# Run simulated annealing algorithm
SimulatedAnnealing(board).run()