out how fibonacci numbers are involved in computing their time complexities comparison of heap time complexities it is clear that the more complex binomial and fibonacci heaps offer average time complexity advantages over simple binary heap trees the following table summarizes the average time complexities of the crucial heap operationsheap type binary binomial fibonacci insert (log no( ( delete (log no(log no(log nmerge (no(log no( heapify (no(no(nup priority (log no(log no( obviously it will depend on the application in question whether using more complicated heap is worth the effort we shall see later that fibonacci heaps are important in practice because they are used in the most efficient versions of many algorithms that can be implemented using priority queuessuch as dijkstra' algorithm for finding shortest routesand prim' algorithm for finding minimal spanning trees