多源 BFS 的工作方式与常规 BFS 完全相同,但不是从单个节点开始,而是将所有源 (A) 放在队列的开头。也就是说,遍历网格以找到所有 A 并在距离 0 处使用所有它们初始化 BFS 队列。然后照常继续 BFS。
这是一个 Python 实现示例:
from collections import deque
from itertools import product
def get_distance():
grid = [['0', '0', '0', '0', '0', '0', '0', '0', '0'],
['0', 'A', 'A', 'A', '0', '0', '0', '0', '0'],
['0', 'A', 'A', '0', '0', '0', '0', '0', '0'],
['0', 'A', 'A', 'A', '0', '0', '0', '0', '0'],
['0', '0', '0', '0', '0', '0', '0', '0', '0'],
['0', '0', '0', '0', '0', '0', '0', '0', '0'],
['0', '0', '0', '0', '0', '0', 'B', '0', '0'],
['0', '0', '0', '0', '0', 'B', 'B', 'B', '0'],
['0', '0', '0', '0', '0', 'B', 'B', 'B', 'B']]
R = C = 9 # dimensions of the grid
queue = deque()
visited = [[False]*C for _ in range(R)]
distance = [[None]*C for _ in range(R)]
for row, col in product(range(R), range(C)):
if grid[row][col] == 'A':
queue.append((row, col))
distance[row][col] = 0
visited[row][col] = True
while queue:
r, c = queue.popleft()
for row, col in ((r-1, c), (r, c+1), (r+1, c), (r, c-1)): # all directions
if 0 <= row < R and 0 <= col < C and not visited[row][col]:
distance[row][col] = distance[r][c] + 1
if grid[row][col] == 'B':
return distance[row][col]
visited[row][col] = True
queue.append((row, col))
print(get_distance()) # 6