We're given an unweighted undirected graph G = (V, E) where |V| <= 40,000 and |E| <= 106. We're also given four vertices a, b, a', b'. Is there a way to find two node-disjoint paths a -> a' and b -> b' such that the sum of their lengths is minimum?
My first thought was to first find the shortest path a -> a', delete it from the graph, and then find the shortest path b -> b'. I don't think this greedy approach would work.
Note: Throughout the application, a and b are fixed, while a' and b' change at each query, so a solution that uses precomputing in order to provide efficient querying would be preferable. Note also that only the minimum sum of lengths is needed, not the actual paths.
Any help, ideas, or suggestions would be extremely appreciated. Thanks a lot in advance!
Dijkstra's algorithm (/ˈdaɪkstrəz/ DYKE-strəz) is an algorithm for finding the shortest paths between nodes in a graph, which may represent, for example, road networks. It was conceived by computer scientist Edsger W.
Bellman Ford's Algorithm: Bellman Ford's algorithm is used to find the shortest paths from the source vertex to all other vertices in a weighted graph.
This may be reduced to the shortest edge-disjoint paths problem:
Now if a = b or a' = b', you get exactly the same problem as in your previous question (which is Minimum-cost flow problem and may be solved by assigning flow capacity for each edge equal to 1, then searching for a minimum-cost flow between a and b with flow=2). If a != b, you just create a common source node and connect both a and b to it. If a' != b', do the same with a common destination node.
But if a != b and a' != b', minimum-cost flow problem is not applicable. Instead this problem may be solved as Multi-commodity flow problem.
My previous (incorrect) solution was to connect both pairs of (a, b) and (a', b') to common source/destination nodes, then to find a minimum-cost flow. Following graph is a counter-example for this approach:
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