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transitive reduction algorithm: pseudocode?

Asked 2009-11-06T22:33:08.890
45

I have been looking for an algorithm to perform a transitive reduction on a graph, but without success. There's nothing in my algorithms bible (Introduction To Algorithms by Cormen et al) and whilst I've seen plenty of transitive closure pseudocode, I haven't been able to track down anything for a reduction. The closest I've got is that there is one in "Algorithmische Graphentheorie" by Volker Turau (ISBN:978-3-486-59057-9), but unfortunately I don't have access to this book! Wikipedia is unhelpful and Google is yet to turn up anything. :^(

Does anyone know of an algorithm for performing a transitive reduction?

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2 Answers

7

The basic gist of the transitive reduction algorithm I used is


foreach x in graph.vertices
   foreach y in graph.vertices
      foreach z in graph.vertices
         delete edge xz if edges xy and yz exist

The transitive closure algorithm I used in the same script is very similar but the last line is


         add edge xz if edges xy and yz OR edge xz exist
answered 2010-03-03T14:49:42.797
6

Based on the reference provided by Alan Donovan, which says you should use the path matrix (which has a 1 if there is a path from node i to node j) instead of the adjacency matrix (which has a 1 only if there is an edge from node i to node j).

Some sample python code follows below to show the differences between the solutions

def prima(m, title=None):
    """ Prints a matrix to the terminal """
    if title:
        print title
    for row in m:
        print ', '.join([str(x) for x in row])
    print ''

def path(m):
    """ Returns a path matrix """
    p = [list(row) for row in m]
    n = len(p)
    for i in xrange(0, n):
        for j in xrange(0, n):
            if i == j:
                continue
            if p[j][i]:
                for k in xrange(0, n):
                    if p[j][k] == 0:
                        p[j][k] = p[i][k]
    return p

def hsu(m):
    """ Transforms a given directed acyclic graph into its minimal equivalent """
    n = len(m)
    for j in xrange(n):
        for i in xrange(n):
            if m[i][j]:
                for k in xrange(n):
                    if m[j][k]:
                        m[i][k] = 0

m = [   [0, 1, 1, 0, 0],
        [0, 0, 0, 0, 0],
        [0, 0, 0, 1, 1],
        [0, 0, 0, 0, 1],
        [0, 1, 0, 0, 0]]

prima(m, 'Original matrix')
hsu(m)
prima(m, 'After Hsu')

p = path(m)
prima(p, 'Path matrix')
hsu(p)
prima(p, 'After Hsu')

Output:

Adjacency matrix
0, 1, 1, 0, 0
0, 0, 0, 0, 0
0, 0, 0, 1, 1
0, 0, 0, 0, 1
0, 1, 0, 0, 0

After Hsu
0, 1, 1, 0, 0
0, 0, 0, 0, 0
0, 0, 0, 1, 0
0, 0, 0, 0, 1
0, 1, 0, 0, 0

Path matrix
0, 1, 1, 1, 1
0, 0, 0, 0, 0
0, 1, 0, 1, 1
0, 1, 0, 0, 1
0, 1, 0, 0, 0

After Hsu
0, 0, 1, 0, 0
0, 0, 0, 0, 0
0, 0, 0, 1, 0
0, 0, 0, 0, 1
0, 1, 0, 0, 0
answered 2013-05-03T11:16:02.203

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