New symmetric Graph concept.
New symmetric list and smart graph.
Symmetric Graph tests based on the Graph Tests.
2 * src/hugo/suurballe.h - Part of HUGOlib, a generic C++ optimization library
4 * Copyright (C) 2004 Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
5 * (Egervary Combinatorial Optimization Research Group, EGRES).
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.
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
17 #ifndef HUGO_SUURBALLE_H
18 #define HUGO_SUURBALLE_H
22 ///\brief An algorithm for finding k paths of minimal total length.
25 #include <hugo/maps.h>
27 #include <hugo/min_cost_flow.h>
31 /// \addtogroup flowalgs
34 ///\brief Implementation of an algorithm for finding k edge-disjoint paths between 2 nodes
35 /// of minimal total length
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).
42 ///\warning Length values should be nonnegative.
44 ///\param Graph The directed graph type the algorithm runs on.
45 ///\param LengthMap The type of the length map (values should be nonnegative).
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
56 ///\author Attila Bernath
57 template <typename Graph, typename LengthMap>
61 typedef typename LengthMap::ValueType Length;
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;
69 typedef ConstMap<Edge,int> ConstMap;
75 //This is the capacity map for the mincostflow problem
77 //This MinCostFlow instance will actually solve the problem
78 MinCostFlow<Graph, LengthMap, ConstMap> mincost_flow;
80 //Container to store found paths
81 std::vector< std::vector<Edge> > paths;
86 /// The constructor of the class.
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){}
93 ///Runs the algorithm.
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.
99 ///\param s The source node.
100 ///\param t The target node.
101 ///\param k How many paths are we looking for?
103 int run(Node s, Node t, int k) {
105 int i = mincost_flow.run(s,t,k);
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.
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);
117 for(typename Graph::EdgeIt e(G); e!=INVALID; ++e)
118 reversed[e] = mincost_flow.getFlow()[e];
123 for (int j=0; j<i; ++j){
132 while (!reversed[e]){
136 paths[j].push_back(e);
137 //total_length += length[e];
138 reversed[e] = 1-reversed[e];
146 ///Returns the total length of the paths
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();
155 ///Returns the found flow.
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;}
162 /// Returns the optimal dual solution
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;}
169 ///Checks whether the complementary slackness holds.
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.
177 bool checkComplementarySlackness(){
178 return mincost_flow.checkComplementarySlackness();
181 ///Read the found paths.
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).
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){
197 if (j>paths.size()-1){
200 typename Path::Builder B(p);
201 for(typename std::vector<Edge>::iterator i=paths[j].begin();
202 i!=paths[j].end(); ++i ){
215 #endif //HUGO_SUURBALLE_H