Global Price Updates Help

Abstract

Periodic global updates of dual variables have been shown to yield a substantial speed advantage in implementations of push-relabel algorithms for the maximum flow and minimum cost flow problems. In this paper, we show that in the context of the bipartite matching and assignment problems, global updates yield a theoretical improvement as well. For bipartite matching, a push-relabel algorithm that uses global updates runs in $O\big(\sqrt n m\frac{\log(n^2/m)}{\log n}\big)$ time (matching the best bound known) and performs worse by a factor of $\sqrt n$ without the updates. A similar result holds for the assignment problem, for which an algorithm that assumes integer costs in the range $[\,-C,\ldots, C\,]$ and that runs in time $O(\sqrt n m\log(nC))$ (matching the best cost-scaling bound known) is presented.