조합 최적화 - 최소 절단 문제

최소 절단 문제

실행 방법

Signature: nx.minimum_cut(G, s, t, capacity='capacity', flow_func=None, **kwargs)
Docstring:
Compute the value and the node partition of a minimum (s, t)-cut.

# CSVデータ
import pandas as pd, networkx as nx
from ortoolpy import graph_from_table, networkx_draw
tbn = pd.read_csv('data/node0.csv')
tbe = pd.read_csv('data/edge0.csv')
g = graph_from_table(tbn, tbe)
networkx_draw(g)
nx.minimum_cut(g, 5, 2)
>>>
(6, ({0, 1, 3, 4, 5}, {2}))

# 乱数データ
import networkx as nx, matplotlib.pyplot as plt
from ortoolpy import networkx_draw
g = nx.random_graphs.fast_gnp_random_graph(10, 0.3, 1)
for i, j in g.edges():
    g.adj[i][j]['capacity'] = 1
pos = networkx_draw(g, nx.spring_layout(g))
nx.draw_networkx_edges(g, pos)
nx.minimum_cut(g, 5, 6)
>>>
(3, ({2, 5}, {0, 1, 3, 4, 6, 7, 8, 9}))

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