We give a deterministic O(mlog2/3n)-time algorithm for single-source shortest paths (SSSP) on directed graphs with real non-negative edge weights in the comparison-addition model. This is the first result to break the O(m+nlogn) time bound of Dijkstra's algorithm on sparse graphs, showing that Dijkstra's algorithm is not optimal for SSSP.
I'm continually amazed by the asymptotic complexity of union-find, which is O(alpha(n)), where alpha(x) is the inverse of the Ackermann function (and n the number of sets you union). In other words, O(6) or so as long as your inputs fit into the observable universe.
There's definitely a divide on who sees what sort of algorithms. The subject of this article is in Graph Theory space, which a lot of us get even without trying (I dabbled in TSP for a while because it's a difficult distributed programming problem and I wanted to explore the space for that reason).
But if you're not implementing AI or game engines, some of the linear algebra space may be a road less traveled.
We give a deterministic O(mlog2/3n)-time algorithm for single-source shortest paths (SSSP) on directed graphs with real non-negative edge weights in the comparison-addition model. This is the first result to break the O(m+nlogn) time bound of Dijkstra's algorithm on sparse graphs, showing that Dijkstra's algorithm is not optimal for SSSP.