In practice, the auction algorithm has proved very effective for assignment problems. Computational
studies [BCT91], [BeE88] have shown that it is often substantially faster than its closest competitors,
particularly for sparse problems. The speedup factor typically increases with the problem size. As the
problem density increases the speedup factor tends to decrease and for fully dense problems the auction
algorithm is roughly competitive to methods that combine the primal-dual (or sequential shortest path
method) with an extensive initialization procedure based on the naive auction algorithm of Section 2
[Ber81], [JoV87]. A recent extensive computational study [Cas92] explores the behavior of various auction
algorithms for randomly generated problems with a broad variety of different structures.