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Single-source shortest-path algorithms

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Single-source shortest-path algorithms - Neptune Analytics
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A single-source-shortest-path algorithm finds the shortest paths (or the distance of the shortest paths) between a given vertex and all reachable vertices in the graph (including itself).

By determining the most efficient routes from a single starting node to all other nodes in the graph, single-source-shortest-path can be used calculate the shortest distances or lowest cost required to reach each destination. This is applicable in GPS systems to find the fastest routes between a starting point and differeent destinations, and in logistics to optimize delivery routes, and in transportation planning for efficient navigation through road networks.

Neptune Analytics supports the following single-source-shortest-path (SSSP) algorithms:

  • .sssp.bellmanFord   –   Computes the shortest path distances from a source vertex to all other vertices in the graph using the Bellman-Ford algorithm. Positive edge weights must be provided using the edgeWeightProperty, and the traversal direction must not be set to both.

  • .sssp.bellmanFord.parents   –   Identifies the parent vertices along the shortest paths from the source vertex to all other vertices in the graph using the Bellman-Ford algorithm. Positive edge weights must be provided using the edgeWeightProperty, and the traversal direction must not be set to both.

  • .sssp.bellmanFord.path   –   Finds the shortest path between a given source vertex and a target vertex in the graph using the Bellman-Ford algorithm. To compute all shortest paths from a given source vertex, the regular SSSP algorithm can be used. Positive edge weights must be provided using the edgeWeightProperty, and the traversal direction must not be set to both.

  • .sssp.deltaStepping   –   Computes the shortest path distances from a source vertex to all other vertices in the graph using a delta-stepping algorithm. Positive edge weights must be provided using the edgeWeightProperty, and the traversal direction must not be set to both.

  • .sssp.deltaStepping.parents   –   Identifies the parent vertices along the shortest paths from the source vertex to all other vertices in the graph using a delta-stepping algorithm. Positive edge weights must be provided using the edgeWeightProperty, and the traversal direction must not be set to both.

  • .sssp.deltaStepping.path   –   Finds the shortest path between a given source vertex and a target vertex in the graph using the delta-stepping algorithm. To compute all shortest paths from a given source vertex, the regular SSSP algorithm can be used. Positive edge weights must be provided using the edgeWeightProperty, and the traversal direction must not be set to both.

  • .topksssp   –   The TopK hop-limited single source shortest path algorithm finds the single-source weighted shortest paths starting from a source vertex to all its maxDepth neighbors. The distance or cost from the source vertex to each target vertex is accumulated on the edge weights of the path. The topK distances of the paths are sorted in descending or ascending order.

    The algorithm can be run unweighted as well as weighted. When you run it unweighted, it's equivalent to .bfs.levels.

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