Priority queues are some of the most fundamental data structures. They are used directly for, say, task scheduling in operating systems. Moreover, they are essential to greedy algorithms. We study the complexity of priority queue operations on a RAM with arbitrary word size. We present exponential improvements over previous bounds, and we show tight relations to sorting. Our first result is a RAM priority queue supporting insert and extract-min operations in worst case time O(log log n) where n is the current number of keys in the queue. This is an exponential improvement over the O( p log n) bound of Fredman and Willard from STOC'90. Our algorithm is simple, and it only uses AC 0 operations, meaning that there is no hidden time dependency on the word size. Plugging this priority queue into Dijkstra's algorithm gives an O(m log log m) algorithm for the single source shortest path problem on a graph with m edges, as compared with the previous O(m p log m) bound based on Fredman...

The single source shortest paths problem (SSSP) is one of the classic problems in algorithmic graph theory: given a weighted graph G with a source vertex s, find the shortest path from s to all other vertices in the graph. Since 1959 all theoretical developments in SSSP have been based on Dijkstra's algorithm, visiting the vertices in order of increasing distance from s. Thus, any implementation of Dijkstra 's algorithm sorts the vertices according to their distances from s. However, we do not know how to sort in linear time. Here, a deterministic linear time and linear space algorithm is presented for the undirected single source shortest paths problem with integer weights. The algorithm avoids the sorting bottle-neck by building a hierechical bucketing structure, identifying vertex pairs that may be visited in any order. 1 Introduction Let G = (V; E), jV j = n, jEj = m, be an undirected connected graph with an integer edge weight function ` : E ! N and a distinguished source vertex...