Negative-Weight Single-Source Shortest Paths in Near-linear Time

We present a randomized algorithm that computes single-source shortest paths (SSSP) in O(mlog(8)(n) logW) time when edge weights are integral and can be negative. This essentially resolves the classic negative-weight SSSP problem. The previous bounds are (O) over tilde ((m + n(1.5)) logW) [BLNPSSSW FOCS'20] and m(4/3+o(1)) logW [AMV FOCS'20]. Near-linear time algorithms were known previously only for the special case of planar directed graphs [Fakcharoenphol and Rao FOCS'01]. In contrast to all recent developments that rely on sophisticated continuous optimization methods and dynamic algorithms, our algorithm is simple: it requires only a simple graph decomposition and elementary combinatorial tools. In fact, ours is the first combinatorial algorithm for negative-weight SSSP to break through the classic (O) over tilde (m root n logW) bound from over three decades ago [Gabow and Tarjan SICOMP'89].