S

m

p

```
"""
Ford-Fulkerson Algorithm for Maximum Flow Problem
* https://en.wikipedia.org/wiki/Ford%E2%80%93Fulkerson_algorithm
Description:
(1) Start with initial flow as 0
(2) Choose the augmenting path from source to sink and add the path to flow
"""
graph = [
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def breadth_first_search(graph: list, source: int, sink: int, parents: list) -> bool:
"""
This function returns True if there is a node that has not iterated.
Args:
graph: Adjacency matrix of graph
source: Source
sink: Sink
parents: Parent list
Returns:
True if there is a node that has not iterated.
>>> breadth_first_search(graph, 0, 5, [-1, -1, -1, -1, -1, -1])
True
>>> breadth_first_search(graph, 0, 6, [-1, -1, -1, -1, -1, -1])
Traceback (most recent call last):
...
IndexError: list index out of range
"""
visited = [False] * len(graph) # Mark all nodes as not visited
queue = [] # breadth-first search queue
# Source node
queue.append(source)
visited[source] = True
while queue:
u = queue.pop(0) # Pop the front node
# Traverse all adjacent nodes of u
for ind, node in enumerate(graph[u]):
if visited[ind] is False and node > 0:
queue.append(ind)
visited[ind] = True
parents[ind] = u
return visited[sink]
def ford_fulkerson(graph: list, source: int, sink: int) -> int:
"""
This function returns the maximum flow from source to sink in the given graph.
CAUTION: This function changes the given graph.
Args:
graph: Adjacency matrix of graph
source: Source
sink: Sink
Returns:
Maximum flow
>>> test_graph = [
... [0, 16, 13, 0, 0, 0],
... [0, 0, 10, 12, 0, 0],
... [0, 4, 0, 0, 14, 0],
... [0, 0, 9, 0, 0, 20],
... [0, 0, 0, 7, 0, 4],
... [0, 0, 0, 0, 0, 0],
... ]
>>> ford_fulkerson(test_graph, 0, 5)
23
"""
# This array is filled by breadth-first search and to store path
parent = [-1] * (len(graph))
max_flow = 0
# While there is a path from source to sink
while breadth_first_search(graph, source, sink, parent):
path_flow = int(1e9) # Infinite value
s = sink
while s != source:
# Find the minimum value in the selected path
path_flow = min(path_flow, graph[parent[s]][s])
s = parent[s]
max_flow += path_flow
v = sink
while v != source:
u = parent[v]
graph[u][v] -= path_flow
graph[v][u] += path_flow
v = parent[v]
return max_flow
if __name__ == "__main__":
from doctest import testmod
testmod()
print(f"{ford_fulkerson(graph, source=0, sink=5) = }")
```