Added the function isFinite(), and replaced the calls to finite() with it.
This was necessary because finite() is not a standard function. Neither can
we use its standard counterpart isfinite(), because it was introduced only
in C99, and therefore it is not supplied by all C++ implementations.
3 * This file is a part of LEMON, a generic C++ optimization library
5 * Copyright (C) 2003-2007
6 * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
7 * (Egervary Research Group on Combinatorial Optimization, EGRES).
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.
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
19 #ifndef LEMON_SUURBALLE_H
20 #define LEMON_SUURBALLE_H
22 ///\ingroup shortest_path
24 ///\brief An algorithm for finding k paths of minimal total length.
27 #include <lemon/maps.h>
29 #include <lemon/path.h>
30 #include <lemon/ssp_min_cost_flow.h>
34 /// \addtogroup shortest_path
37 ///\brief Implementation of an algorithm for finding k edge-disjoint
38 /// paths between 2 nodes of minimal total length
40 /// The class \ref lemon::Suurballe implements
41 /// an algorithm for finding k edge-disjoint paths
42 /// from a given source node to a given target node in an
43 /// edge-weighted directed graph having minimal total weight (length).
45 ///\warning Length values should be nonnegative!
47 ///\param Graph The directed graph type the algorithm runs on.
48 ///\param LengthMap The type of the length map (values should be nonnegative).
50 ///\note It it questionable whether it is correct to call this method after
51 ///%Suurballe for it is just a special case of Edmonds' and Karp's algorithm
52 ///for finding minimum cost flows. In fact, this implementation just
53 ///wraps the SspMinCostFlow algorithms. The paper of both %Suurballe and
54 ///Edmonds-Karp published in 1972, therefore it is possibly right to
55 ///state that they are
56 ///independent results. Most frequently this special case is referred as
57 ///%Suurballe method in the literature, especially in communication
59 ///\author Attila Bernath
60 template <typename Graph, typename LengthMap>
64 typedef typename LengthMap::Value Length;
66 typedef typename Graph::Node Node;
67 typedef typename Graph::NodeIt NodeIt;
68 typedef typename Graph::Edge Edge;
69 typedef typename Graph::OutEdgeIt OutEdgeIt;
70 typedef typename Graph::template EdgeMap<int> EdgeIntMap;
72 typedef ConstMap<Edge,int> ConstMap;
80 //This is the capacity map for the mincostflow problem
82 //This MinCostFlow instance will actually solve the problem
83 SspMinCostFlow<Graph, LengthMap, ConstMap> min_cost_flow;
85 //Container to store found paths
86 std::vector<SimplePath<Graph> > paths;
91 /// \brief The constructor of the class.
93 /// \param _G The directed graph the algorithm runs on.
94 /// \param _length The length (weight or cost) of the edges.
95 /// \param _s Source node.
96 /// \param _t Target node.
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) { }
101 /// \brief Runs the algorithm.
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
108 /// \param k How many paths are we looking for?
111 int i = min_cost_flow.run(k);
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.
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);
122 for(typename Graph::EdgeIt e(G); e!=INVALID; ++e)
123 reversed[e] = min_cost_flow.getFlow()[e];
127 for (int j=0; j<i; ++j){
134 while (!reversed[e]){
139 reversed[e] = 1-reversed[e];
147 /// \brief Returns the total length of the paths.
149 /// This function gives back the total length of the found paths.
150 Length totalLength(){
151 return min_cost_flow.totalLength();
154 /// \brief Returns the found flow.
156 /// This function returns a const reference to the EdgeMap \c flow.
157 const EdgeIntMap &getFlow() const { return min_cost_flow.flow;}
159 /// \brief Returns the optimal dual solution
161 /// This function returns a const reference to the NodeMap \c
162 /// potential (the dual solution).
163 const EdgeIntMap &getPotential() const { return min_cost_flow.potential;}
165 /// \brief Checks whether the complementary slackness holds.
167 /// This function checks, whether the given solution is optimal.
168 /// Currently this function only checks optimality, doesn't bother
169 /// with feasibility. It is meant for testing purposes.
170 bool checkComplementarySlackness(){
171 return min_cost_flow.checkComplementarySlackness();
174 typedef SimplePath<Graph> Path;
176 /// \brief Read the found paths.
178 /// This function gives back the \c j-th path in argument p.
179 /// Assumes that \c run() has been run and nothing has changed
182 /// \warning It is assumed that \c p is constructed to be a path
183 /// of graph \c G. If \c j is not less than the result of
184 /// previous \c run, then the result here will be an empty path
185 /// (\c j can be 0 as well).
187 /// \param j Which path you want to get from the found paths (in a
188 /// real application you would get the found paths iteratively).
189 Path path(int j) const {
193 /// \brief Gives back the number of the paths.
195 /// Gives back the number of the constructed paths.
196 int pathNum() const {
206 #endif //LEMON_SUURBALLE_H