Label-Correcting Shortest Path Algorithms Revisited

Summary

In this paper we study label-correcting algorithms, which are routinely used to solve single-source shortest path problems. Several variants of label-correcting algorithms have been proposed in the literature, differing primarily in the strategy implemented to handle the candidate list of nodes. In particular, we study both one-list and two-list versions of the basic label-correcting algorithm; these variants implement either one or two lists to manage the set of candidate nodes. We examine the theoretical complexity and empirical behavior of these algorithms. In contrast to previous studies of shortest path algorithms, our focus is on explaining observed empirical performance in terms of certain intrinisic properties of the algorithms (namely, “sharpness” and “maturity”). In addition, a new variant of the label-correcting algorithm is proposed (PRED), which insures a type of “local sharpness” relative to the candidate list. Computational evidence suggests that this new algorithm, in both one-list and two-list versions, performs quite well in practice and deserves further study.