Finding the exact shortest path on a nationwide network dataset is time-consuming due to the large number of edges that need to be searched. To improve performance, network datasets can model the natural hierarchy in a transportation system where driving on an interstate highway is preferable to driving on local roads. Once a hierarchical network has been created, a modification of the bidirectional Dijkstra is used to compute a route between an origin and a destination.
The overall objective here is to minimize the impedance while favoring the higher-order hierarchies present in the network. It does this by simultaneously searching from both origin and destination locations, as well as connection or entry points into higher-level roads, then searching the higher-level roads until segments from both origin and destination meet. As the search is restricted to the upper hierarchy, a smaller number of edges are searched, resulting in faster performance. Note that this is a heuristic algorithm; its goal is fast performance and good solutions, but it does not guarantee that the shortest path will be found. For this heuristic to be successful, the top-level hierarchy must be connected, as it will not descend to a lower level if a dead end is reached.
Generally, it makes sense to use this solver on a hierarchical network where the edge weights are based on travel time. This mimics the way people normally drive on a highway network.