lemon/suurballe.h
author deba
Tue, 21 Mar 2006 13:45:24 +0000
changeset 2011 1a1bffa615b8
parent 1875 98698b69a902
child 2276 1a8a66b6c6ce
permissions -rw-r--r--
Renaming files
     1 /* -*- C++ -*-
     2  *
     3  * This file is a part of LEMON, a generic C++ optimization library
     4  *
     5  * Copyright (C) 2003-2006
     6  * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
     7  * (Egervary Research Group on Combinatorial Optimization, EGRES).
     8  *
     9  * Permission to use, modify and distribute this software is granted
    10  * provided that this copyright notice appears in all copies. For
    11  * precise terms see the accompanying LICENSE file.
    12  *
    13  * This software is provided "AS IS" with no warranty of any kind,
    14  * express or implied, and with no claim as to its suitability for any
    15  * purpose.
    16  *
    17  */
    18 
    19 #ifndef LEMON_SUURBALLE_H
    20 #define LEMON_SUURBALLE_H
    21 
    22 ///\ingroup flowalgs
    23 ///\file
    24 ///\brief An algorithm for finding k paths of minimal total length.
    25 
    26 
    27 #include <lemon/maps.h>
    28 #include <vector>
    29 #include <lemon/min_cost_flow.h>
    30 
    31 namespace lemon {
    32 
    33 /// \addtogroup flowalgs
    34 /// @{
    35 
    36   ///\brief Implementation of an algorithm for finding k edge-disjoint paths between 2 nodes 
    37   /// of minimal total length 
    38   ///
    39   /// The class \ref lemon::Suurballe implements
    40   /// an algorithm for finding k edge-disjoint paths
    41   /// from a given source node to a given target node in an
    42   /// edge-weighted directed graph having minimal total weight (length).
    43   ///
    44   ///\warning Length values should be nonnegative!
    45   /// 
    46   ///\param Graph The directed graph type the algorithm runs on.
    47   ///\param LengthMap The type of the length map (values should be nonnegative).
    48   ///
    49   ///\note It it questionable whether it is correct to call this method after
    50   ///%Suurballe for it is just a special case of Edmonds' and Karp's algorithm
    51   ///for finding minimum cost flows. In fact, this implementation just
    52   ///wraps the MinCostFlow algorithms. The paper of both %Suurballe and
    53   ///Edmonds-Karp published in 1972, therefore it is possibly right to
    54   ///state that they are
    55   ///independent results. Most frequently this special case is referred as
    56   ///%Suurballe method in the literature, especially in communication
    57   ///network context.
    58   ///\author Attila Bernath
    59   template <typename Graph, typename LengthMap>
    60   class Suurballe{
    61 
    62 
    63     typedef typename LengthMap::Value Length;
    64     
    65     typedef typename Graph::Node Node;
    66     typedef typename Graph::NodeIt NodeIt;
    67     typedef typename Graph::Edge Edge;
    68     typedef typename Graph::OutEdgeIt OutEdgeIt;
    69     typedef typename Graph::template EdgeMap<int> EdgeIntMap;
    70 
    71     typedef ConstMap<Edge,int> ConstMap;
    72 
    73     const Graph& G;
    74 
    75     Node s;
    76     Node t;
    77 
    78     //Auxiliary variables
    79     //This is the capacity map for the mincostflow problem
    80     ConstMap const1map;
    81     //This MinCostFlow instance will actually solve the problem
    82     MinCostFlow<Graph, LengthMap, ConstMap> min_cost_flow;
    83 
    84     //Container to store found paths
    85     std::vector< std::vector<Edge> > paths;
    86 
    87   public :
    88 
    89 
    90     /*! \brief The constructor of the class.
    91     
    92     \param _G The directed graph the algorithm runs on. 
    93     \param _length The length (weight or cost) of the edges. 
    94     \param _s Source node.
    95     \param _t Target node.
    96     */
    97     Suurballe(Graph& _G, LengthMap& _length, Node _s, Node _t) : 
    98       G(_G), s(_s), t(_t), const1map(1), 
    99       min_cost_flow(_G, _length, const1map, _s, _t) { }
   100 
   101     ///Runs the algorithm.
   102 
   103     ///Runs the algorithm.
   104     ///Returns k if there are at least k edge-disjoint paths from s to t.
   105     ///Otherwise it returns the number of edge-disjoint paths found 
   106     ///from s to t.
   107     ///
   108     ///\param k How many paths are we looking for?
   109     ///
   110     int run(int k) {
   111       int i = min_cost_flow.run(k);
   112 
   113       //Let's find the paths
   114       //We put the paths into stl vectors (as an inner representation). 
   115       //In the meantime we lose the information stored in 'reversed'.
   116       //We suppose the lengths to be positive now.
   117 
   118       //We don't want to change the flow of min_cost_flow, so we make a copy
   119       //The name here suggests that the flow has only 0/1 values.
   120       EdgeIntMap reversed(G); 
   121 
   122       for(typename Graph::EdgeIt e(G); e!=INVALID; ++e) 
   123 	reversed[e] = min_cost_flow.getFlow()[e];
   124       
   125       paths.clear();
   126       paths.resize(k);
   127       for (int j=0; j<i; ++j){
   128 	Node n=s;
   129 
   130 	while (n!=t){
   131 
   132 	  OutEdgeIt e(G, n);
   133 	  
   134 	  while (!reversed[e]){
   135 	    ++e;
   136 	  }
   137 	  n = G.target(e);
   138 	  paths[j].push_back(e);
   139 	  reversed[e] = 1-reversed[e];
   140 	}
   141 	
   142       }
   143       return i;
   144     }
   145 
   146     
   147     ///Returns the total length of the paths.
   148     
   149     ///This function gives back the total length of the found paths.
   150     Length totalLength(){
   151       return min_cost_flow.totalLength();
   152     }
   153 
   154     ///Returns the found flow.
   155 
   156     ///This function returns a const reference to the EdgeMap \c flow.
   157     const EdgeIntMap &getFlow() const { return min_cost_flow.flow;}
   158 
   159     /// Returns the optimal dual solution
   160     
   161     ///This function returns a const reference to the NodeMap
   162     ///\c potential (the dual solution).
   163     const EdgeIntMap &getPotential() const { return min_cost_flow.potential;}
   164 
   165     ///Checks whether the complementary slackness holds.
   166 
   167     ///This function checks, whether the given solution is optimal.
   168     ///Currently this function only checks optimality,
   169     ///doesn't bother with feasibility.
   170     ///It is meant for testing purposes.
   171     bool checkComplementarySlackness(){
   172       return min_cost_flow.checkComplementarySlackness();
   173     }
   174 
   175     ///Read the found paths.
   176     
   177     ///This function gives back the \c j-th path in argument p.
   178     ///Assumes that \c run() has been run and nothing has changed since then.
   179     /// \warning It is assumed that \c p is constructed to
   180     ///be a path of graph \c G.
   181     ///If \c j is not less than the result of previous \c run,
   182     ///then the result here will be an empty path (\c j can be 0 as well).
   183     ///
   184     ///\param Path The type of the path structure to put the result to (must meet lemon path concept).
   185     ///\param p The path to put the result to.
   186     ///\param j Which path you want to get from the found paths (in a real application you would get the found paths iteratively).
   187     template<typename Path>
   188     void getPath(Path& p, size_t j){
   189 
   190       p.clear();
   191       if (j>paths.size()-1){
   192 	return;
   193       }
   194       typename Path::Builder B(p);
   195       for(typename std::vector<Edge>::iterator i=paths[j].begin(); 
   196 	  i!=paths[j].end(); ++i ){
   197 	B.pushBack(*i);
   198       }
   199 
   200       B.commit();
   201     }
   202 
   203   }; //class Suurballe
   204 
   205   ///@}
   206 
   207 } //namespace lemon
   208 
   209 #endif //LEMON_SUURBALLE_H