Abstract

We introduce the heap-on-top (hot) priority queue data structure that combines the multi-level bucket data structure of Denardo and Fox [9] and a heap. We use the new data structure to obtain an O(m+n(logC) 1 3 +ffl ) expected time implementation of Dijkstra's shortest path algorithm [11], improving the previous bounds. This work was done while the author was visiting NEC Research Institute. 1 Introduction A priority queue is a data structure that maintains a set of elements and supports operations insert, decrease-key, and extract-min. Priority queues are fundamental data structures with many applications. Typical applications include graph algorithms (e.g. [12]) and event simulation (e.g. [5]). An important subclass of priority queues, used in applications such as event simulation and in Dijkstra's shortest path algorithm [11], are monotone priority queues. A priority queue is monotone if keys of elements on the queue are at least as big as the key of the latest element extr...

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