Class ContractionHierarchyPrecomputation<V,E>

java.lang.Object
org.jgrapht.alg.shortestpath.ContractionHierarchyPrecomputation<V,E>
Type Parameters:
V - the graph vertex type
E - the graph edge type

public class ContractionHierarchyPrecomputation<V,E> extends Object
Parallel implementation of the contraction hierarchy route planning precomputation technique.

The original algorithm is described the article: Robert Geisberger, Peter Sanders, Dominik Schultes, and Daniel Delling. 2008. Contraction hierarchies: faster and simpler hierarchical routing in road networks. In Proceedings of the 7th international conference on Experimental algorithms (WEA'08), Catherine C. McGeoch (Ed.). Springer-Verlag, Berlin, Heidelberg, 319-333.

Parallel version of the algorithm is described in the article: Vetter, Christian. "Parallel Time-Dependent Contraction Hierarchies." (2009).

This algorithm speeds up shortest paths computation by contracting graph vertices. To contract a vertex means to remove it from the graph in such a way that shortest paths in the remaining overlay graph are preserved. This property is achieved by replacing paths of the form $\langle u, v, w\rangle$ by a shortcut edge $(u, w)$. Note that the shortcut $(u, w)$ is only required if $\langle u, v, w\rangle$ is the only shortest path from $u$ to $w$.

Contraction is performed as follows. First a priority is computed for each vertex in the graph. This implementation uses edge quotient, complexity quotient and hierarchical depth metrics for computing priority. A hierarchy is then generated by iteratively contracting independent sets of vertices. A vertex is independent iff it`s priority is less than the priority of every vertex in its 2-neighbourhood. A 2-neighbourhood of a vertex $v$ is defined as a set of vertices that are reachable from $v$ using at most 2 hops. After contraction each vertex gets its unique contraction level - its position in the computed hierarchy. Finally, after all vertices are contracted each edge is set to be either upward if its source has lower level that its target, or downward if vice versa.

Computing initial priorities, independent sets and shortcuts, updating neighbours priorities and marking upward edges is performed in parallel what gives this implementation performance speedup comparing to the sequential approach.

For parallelization, this implementation relies on the ThreadPoolExecutor which is supplied to this algorithm from outside.

Author:
Semen Chudakov
  • Constructor Details

    • ContractionHierarchyPrecomputation

      public ContractionHierarchyPrecomputation(Graph<V,E> graph, ThreadPoolExecutor executor)
      Constructs a new instance of the algorithm for a given graph and executor. It is up to a user of this algorithm to handle the creation and termination of the provided executor. For utility methods to manage a ThreadPoolExecutor see ConcurrencyUtil.
      Parameters:
      graph - graph
      executor - executor which will be used for parallelization
    • ContractionHierarchyPrecomputation

      public ContractionHierarchyPrecomputation(Graph<V,E> graph, Supplier<Random> randomSupplier, ThreadPoolExecutor executor)
      Constructs a new instance of the algorithm for a given graph, randomSupplier and executor. Provided randomSupplier should return different random generators instances, because they are used by different threads. It is up to a user of this algorithm to handle the creation and termination of the provided executor. Utility methods to manage a ThreadPoolExecutor see ConcurrencyUtil.
      Parameters:
      graph - graph
      randomSupplier - supplier for preferable instances of Random
      executor - executor which will be used for parallelization
    • ContractionHierarchyPrecomputation

      public ContractionHierarchyPrecomputation(Graph<V,E> graph, Supplier<Random> randomSupplier, Supplier<org.jheaps.AddressableHeap<Double,ContractionHierarchyPrecomputation.ContractionVertex<V>>> shortcutsSearchHeapSupplier, ThreadPoolExecutor executor)
      Constructs a new instance of the algorithm for a given graph, parallelism, randomSupplier, shortcutsSearchHeapSupplier and executor. Provided randomSupplier should return different random generators instances, because they are used by different threads. It is up to a user of this algorithm to handle the creation and termination of the provided executor. For utility methods to manage a ThreadPoolExecutor see ConcurrencyUtil.
      Parameters:
      graph - graph
      randomSupplier - supplier for preferable instances of Random
      shortcutsSearchHeapSupplier - supplier for the preferable heap implementation.
      executor - executor which will be used for parallelization
  • Method Details