有向图中的最大简单周期

问题描述 投票:1回答:1

Maximum Simple Cycle (product) in a graph

你好,

我已经构建了一个有向图G =(v,e),我想在这个图中找到最大的简单周期,其中边权重乘以而不是相加。我这样做的初始方法是构造一个新的图形,G =(v,e'),其中e'(i,j)= 1 / e(i,j)/ min(e'),然后应用Floyd-Warshall在此图表上找到所有最短路径。我的想法是,在反转图形之后,最大路径将变为最小值,并且如果我们除以最小值,则所有边缘权重将是“正”(> = 1,因为我们是乘法而不是加法)。但是,当我运行算法时(我的Python代码在下面)它似乎不起作用,我想知道是不是因为我的算法根本不起作用或者是因为我的代码中有错误。

#construct G' = (V,dist) for our modified Floyd-Warshall algorithm
# edge weights are initially the inverse of w(u,v). They are then all divided
# by the minimum value to ensure all are >= 1
dist = {}
nxt = {}
minimum = float("inf")
for i in e:
    dist[i] = {}
    nxt[i] = {}
    for j in e[i]:
        dist[i][j] = 1/e[i][j]
        nxt[i][j] = j
        if dist[i][j] < minimum:
            minimum = dist[i][j]

for i in dist:
    for j in dist[i]:
        dist[i][j] /= minimum

# Perform Floyd-Warshall
for k in v:
    for i in v:
        for j in v:
            try:
                one = dist[i][j]
                two = dist[i][k]
                three = dist[k][j]
            except KeyError:
                continue

            if one > two * three:
                dist[i][j] = two * three
                nxt[i][j] = nxt[i][k]

# Find the shortest cycle using shortest paths
minimum = float("inf")
for i in v:
    for j in v:
        if i == j:
            continue
        try:
            one = dist[i][j]
            two = dist[j][i]
        except KeyError:
            continue

        if one * two < minimum:
            minimum = one * two
            pair = [i,j]

def Path(u,v):
    if nxt[u][v] == None:
        return []
    path = [u]
    while u != v:
        u = nxt[u][v]
        path.append(u)
    return path

# Format the cycle for output
p1 = Path(pair[0],pair[1])
p2 = Path(pair[1],pair[0])
p = p1 + p2[1:]
print(p)

# Find the total value of the cycle
value = 1
for i in range(len(p)-1):
    value *= e[p[i]][p[i+1]]

print('The above cycle has a %f%% weight.'  % ((value-1)*100))

我用图G =(V,E)测试了上面的例子,其中

V = {a,b,c,d}, and 
E = {
    (a,b): 1/0.00005718 * 0.9975, 
    (a,c): 1/0.03708270 * 0.9975,
    (a,d): 18590.00000016 * 0.9975, 
    (b,a): 0.00010711 * 0.9975,
    (b,c): 0.00386491 * 0.9975, 
    (c,a): 0.03700994 * 0.9975,
    (c,b): 1/18590.00000017 * 0.9975,
    (c,d): 688.30000000 * 0.9975,
    (d,a): 1/18590.00000017 * 0.9975,
    (d,c): 1/688.30000000 * 0.9975
}

上图的输出是循环[a,d,a]是最好的,重量为86.385309%。但是,正如我们所看到的,循环[a,b,c,a]的权重为148.286055%,这要好得多,这让我相信我的算法错误或者我在某个地方有错误。

任何建议都非常感谢!!

python algorithm graph
1个回答
2
投票

我认为问题不是实现而是算法。实际上,以下四个顶点a,b,c和d以及以下边缘为例:

W(A,B)= 10/3

瓦特(B,C)= 10

瓦特(C,d)= 5

瓦特(d,A)= 10/3

瓦特(d,B)= 5

然后,您的算法将返回有向循环(b,c,d,b),而最优解是(a,b,c,d,a)。

此外,您还应该知道您的问题可能是NP完全的,因为Longest Path problem是NP完全的(即使Shortest Path problem是多项式可解的),所以只有少数希望有一个如此简单的算法来解决您的问题。

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