src/hugo/suurballe.h
changeset 921 818510fa3d99
parent 901 69a8e672acb1
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2:d5134296c3ea -1:000000000000
     1 /* -*- C++ -*-
       
     2  * src/hugo/suurballe.h - Part of HUGOlib, a generic C++ optimization library
       
     3  *
       
     4  * Copyright (C) 2004 Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
       
     5  * (Egervary Combinatorial Optimization Research Group, EGRES).
       
     6  *
       
     7  * Permission to use, modify and distribute this software is granted
       
     8  * provided that this copyright notice appears in all copies. For
       
     9  * precise terms see the accompanying LICENSE file.
       
    10  *
       
    11  * This software is provided "AS IS" with no warranty of any kind,
       
    12  * express or implied, and with no claim as to its suitability for any
       
    13  * purpose.
       
    14  *
       
    15  */
       
    16 
       
    17 #ifndef HUGO_SUURBALLE_H
       
    18 #define HUGO_SUURBALLE_H
       
    19 
       
    20 ///\ingroup flowalgs
       
    21 ///\file
       
    22 ///\brief An algorithm for finding k paths of minimal total length.
       
    23 
       
    24 
       
    25 #include <hugo/maps.h>
       
    26 #include <vector>
       
    27 #include <hugo/min_cost_flow.h>
       
    28 
       
    29 namespace hugo {
       
    30 
       
    31 /// \addtogroup flowalgs
       
    32 /// @{
       
    33 
       
    34   ///\brief Implementation of an algorithm for finding k edge-disjoint paths between 2 nodes 
       
    35   /// of minimal total length 
       
    36   ///
       
    37   /// The class \ref hugo::Suurballe implements
       
    38   /// an algorithm for finding k edge-disjoint paths
       
    39   /// from a given source node to a given target node in an
       
    40   /// edge-weighted directed graph having minimal total weight (length).
       
    41   ///
       
    42   ///\warning Length values should be nonnegative.
       
    43   /// 
       
    44   ///\param Graph The directed graph type the algorithm runs on.
       
    45   ///\param LengthMap The type of the length map (values should be nonnegative).
       
    46   ///
       
    47   ///\note It it questionable if it is correct to call this method after
       
    48   ///%Suurballe for it is just a special case of Edmond's and Karp's algorithm
       
    49   ///for finding minimum cost flows. In fact, this implementation is just
       
    50   ///wraps the MinCostFlow algorithms. The paper of both %Suurballe and
       
    51   ///Edmonds-Karp published in 1972, therefore it is possibly right to
       
    52   ///state that they are
       
    53   ///independent results. Most frequently this special case is referred as
       
    54   ///%Suurballe method in the literature, especially in communication
       
    55   ///network context.
       
    56   ///\author Attila Bernath
       
    57   template <typename Graph, typename LengthMap>
       
    58   class Suurballe{
       
    59 
       
    60 
       
    61     typedef typename LengthMap::ValueType Length;
       
    62     
       
    63     typedef typename Graph::Node Node;
       
    64     typedef typename Graph::NodeIt NodeIt;
       
    65     typedef typename Graph::Edge Edge;
       
    66     typedef typename Graph::OutEdgeIt OutEdgeIt;
       
    67     typedef typename Graph::template EdgeMap<int> EdgeIntMap;
       
    68 
       
    69     typedef ConstMap<Edge,int> ConstMap;
       
    70 
       
    71     //Input
       
    72     const Graph& G;
       
    73 
       
    74     //Auxiliary variables
       
    75     //This is the capacity map for the mincostflow problem
       
    76     ConstMap const1map;
       
    77     //This MinCostFlow instance will actually solve the problem
       
    78     MinCostFlow<Graph, LengthMap, ConstMap> mincost_flow;
       
    79 
       
    80     //Container to store found paths
       
    81     std::vector< std::vector<Edge> > paths;
       
    82 
       
    83   public :
       
    84 
       
    85 
       
    86     /// The constructor of the class.
       
    87     
       
    88     ///\param _G The directed graph the algorithm runs on. 
       
    89     ///\param _length The length (weight or cost) of the edges. 
       
    90     Suurballe(Graph& _G, LengthMap& _length) : G(_G),
       
    91       const1map(1), mincost_flow(_G, _length, const1map){}
       
    92 
       
    93     ///Runs the algorithm.
       
    94 
       
    95     ///Runs the algorithm.
       
    96     ///Returns k if there are at least k edge-disjoint paths from s to t.
       
    97     ///Otherwise it returns the number of found edge-disjoint paths from s to t.
       
    98     ///
       
    99     ///\param s The source node.
       
   100     ///\param t The target node.
       
   101     ///\param k How many paths are we looking for?
       
   102     ///
       
   103     int run(Node s, Node t, int k) {
       
   104 
       
   105       int i = mincost_flow.run(s,t,k);
       
   106     
       
   107 
       
   108       //Let's find the paths
       
   109       //We put the paths into stl vectors (as an inner representation). 
       
   110       //In the meantime we lose the information stored in 'reversed'.
       
   111       //We suppose the lengths to be positive now.
       
   112 
       
   113       //We don't want to change the flow of mincost_flow, so we make a copy
       
   114       //The name here suggests that the flow has only 0/1 values.
       
   115       EdgeIntMap reversed(G); 
       
   116 
       
   117       for(typename Graph::EdgeIt e(G); e!=INVALID; ++e) 
       
   118 	reversed[e] = mincost_flow.getFlow()[e];
       
   119       
       
   120       paths.clear();
       
   121       //total_length=0;
       
   122       paths.resize(k);
       
   123       for (int j=0; j<i; ++j){
       
   124 	Node n=s;
       
   125 	OutEdgeIt e;
       
   126 
       
   127 	while (n!=t){
       
   128 
       
   129 
       
   130 	  G.first(e,n);
       
   131 	  
       
   132 	  while (!reversed[e]){
       
   133 	    ++e;
       
   134 	  }
       
   135 	  n = G.head(e);
       
   136 	  paths[j].push_back(e);
       
   137 	  //total_length += length[e];
       
   138 	  reversed[e] = 1-reversed[e];
       
   139 	}
       
   140 	
       
   141       }
       
   142       return i;
       
   143     }
       
   144 
       
   145     
       
   146     ///Returns the total length of the paths
       
   147     
       
   148     ///This function gives back the total length of the found paths.
       
   149     ///\pre \ref run() must
       
   150     ///be called before using this function.
       
   151     Length totalLength(){
       
   152       return mincost_flow.totalLength();
       
   153     }
       
   154 
       
   155     ///Returns the found flow.
       
   156 
       
   157     ///This function returns a const reference to the EdgeMap \c flow.
       
   158     ///\pre \ref run() must
       
   159     ///be called before using this function.
       
   160     const EdgeIntMap &getFlow() const { return mincost_flow.flow;}
       
   161 
       
   162     /// Returns the optimal dual solution
       
   163     
       
   164     ///This function returns a const reference to the NodeMap
       
   165     ///\c potential (the dual solution).
       
   166     /// \pre \ref run() must be called before using this function.
       
   167     const EdgeIntMap &getPotential() const { return mincost_flow.potential;}
       
   168 
       
   169     ///Checks whether the complementary slackness holds.
       
   170 
       
   171     ///This function checks, whether the given solution is optimal.
       
   172     ///It should return true after calling \ref run() 
       
   173     ///Currently this function only checks optimality,
       
   174     ///doesn't bother with feasibility
       
   175     ///It is meant for testing purposes.
       
   176     ///
       
   177     bool checkComplementarySlackness(){
       
   178       return mincost_flow.checkComplementarySlackness();
       
   179     }
       
   180 
       
   181     ///Read the found paths.
       
   182     
       
   183     ///This function gives back the \c j-th path in argument p.
       
   184     ///Assumes that \c run() has been run and nothing changed since then.
       
   185     /// \warning It is assumed that \c p is constructed to
       
   186     ///be a path of graph \c G.
       
   187     ///If \c j is not less than the result of previous \c run,
       
   188     ///then the result here will be an empty path (\c j can be 0 as well).
       
   189     ///
       
   190     ///\param Path The type of the path structure to put the result to (must meet hugo path concept).
       
   191     ///\param p The path to put the result to 
       
   192     ///\param j Which path you want to get from the found paths (in a real application you would get the found paths iteratively)
       
   193     template<typename Path>
       
   194     void getPath(Path& p, size_t j){
       
   195 
       
   196       p.clear();
       
   197       if (j>paths.size()-1){
       
   198 	return;
       
   199       }
       
   200       typename Path::Builder B(p);
       
   201       for(typename std::vector<Edge>::iterator i=paths[j].begin(); 
       
   202 	  i!=paths[j].end(); ++i ){
       
   203 	B.pushBack(*i);
       
   204       }
       
   205 
       
   206       B.commit();
       
   207     }
       
   208 
       
   209   }; //class Suurballe
       
   210 
       
   211   ///@}
       
   212 
       
   213 } //namespace hugo
       
   214 
       
   215 #endif //HUGO_SUURBALLE_H