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Suppose I had a complete bipartite graph with edges each given some numerical "cost" value. Is there a way to select a subset of those edges such that each vertex on each side of the graph is mapped to each vertex on the other (one to one) and the total "costs" is maximized (or minimized)?

Has anyone ever formulated something equivalent to this?

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    $\begingroup$ Do you mean each vertex on on each side is mapped to a vertex on the other? (not each. The way you wrote it it looks like you're searching for a bi-clique). If that's the case, you should look at 'maximum weighted matching' which has a polynomial time algorithm. $\endgroup$
    – Or Zuk
    May 14, 2011 at 11:56
  • $\begingroup$ Yes, I did mean "a" vertex on the other side, sorry for not being clear enough. And I shall look at that matching you've suggested, thanks very much! $\endgroup$ May 14, 2011 at 12:25

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You are looking for the max-flow-min-cut theorem: http://en.wikipedia.org/wiki/Max-flow_min-cut_theorem

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Looks like you are looking for maximum weighted bipartite matching - if so, see Wikipedia for initial pointers.

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