Combining speed-up techniques for shortest-path computations

Computing a shortest path from one node to another in a directed graph is a very common task in practice. This problem is classically solved by Dijkstra's algorithm. Many techniques are known to speed up this algorithm heuristically, while optimality of the solution can still be guaranteed. In most studies, such techniques are considered individually. The focus of our work is the combination of speed-up techniques for Dijkstra's algorithm. We consider all possible combinations of four known techniques, namely goal-directed search, bi-directed search, multilevel approach, and shortest-path bounding boxes, and show how these can be implemented. In an extensive experimental study we compare the performance of different combinations and analyze how the techniques harmonize when applied jointly. Several real-world graphs from road maps and public transport and two types of generated random graphs are taken into account.