Generic Algorithms for SSSP
      Let G be a directed graph, s a node of G, 
        and cost a cost function on the edges of G. 
        Edge costs may be positive or negative. A single source shortest path 
        algorithm computes the shortest paths from s to all other 
        nodes of G with respect to cost. 
       Remark: Finding the shortest path from one node to one other 
        node is not significantly faster than computing the shortest paths from 
        the source to all other nodes. 
      SHORTEST_PATH_T() is the generic LEDA function for 
        computing single source shortest paths in a directed graph. SHORTEST_PATH_T() 
        is a template function. The template parameter NT can be 
        instantiated with any number type. 
      Example of How 
        to Use SHORTEST_PATH_T() 
      SHORTEST_PATH() is the name of the preinstantiated 
        versions of SHORTEST_PATH_T(). There is one function SHORTEST_PATH() 
        for edge costs of type int and one for double. 
      Example of How 
        to Use SHORTEST_PATH() 
      Important Notice: SHORTEST_PATH() only performs correctly 
        if all arithmetic is performed without rounding errors and without overflows. 
        If you are not sure about this, you should use SHORTEST_PATH_T() 
        with one of the LEDA number types. 
      Running time
      The running time of SHORTEST_PATH_T() and SHORTEST_PATH() 
        for a graph G=(V,E) is 
      
        -  linear in the size of the graph (O(|V|+|E|)) for acyclic graphs
 
        - O(|E|+|V|log|V|) if all edge costs are non-negative
 
        - O(|V||E|) otherwise
 
       
      Tips
      
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      See also:
      Shortest Path Algorithms 
      Checking the Results of an SSSP Algorithm 
      SSSP Algorithm for Acyclic Graphs 
       
      Dijkstra's Algorithm for SSSP 
       Bellman-Ford Algorithm for SSSP  
       
       
      Number Types 
      Graphs and Related Data Types 
      Graph Algorithms 
       
      Manual Entries: 
      Manual 
        Page Shortest Path Algorithms 
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