# HG changeset patch # User deba # Date 1162228934 0 # Node ID 1a8a66b6c6ce3856957ad8255d43019b3b8da9bf # Parent ff46747676edb4e9bc25f29308e344f118fd6cdc Min cost flow is renamed to SspMinCostFlow diff -r ff46747676ed -r 1a8a66b6c6ce lemon/Makefile.am --- a/lemon/Makefile.am Mon Oct 30 16:26:13 2006 +0000 +++ b/lemon/Makefile.am Mon Oct 30 17:22:14 2006 +0000 @@ -76,7 +76,6 @@ lemon/matrix_maps.h \ lemon/max_matching.h \ lemon/min_cost_arborescence.h \ - lemon/min_cost_flow.h \ lemon/min_cut.h \ lemon/mip_glpk.h \ lemon/mip_cplex.h \ @@ -90,6 +89,7 @@ lemon/refptr.h \ lemon/simann.h \ lemon/smart_graph.h \ + lemon/ssp_min_cost_flow.h \ lemon/sub_graph.h \ lemon/suurballe.h \ lemon/tabu_search.h \ diff -r ff46747676ed -r 1a8a66b6c6ce lemon/min_cost_flow.h --- a/lemon/min_cost_flow.h Mon Oct 30 16:26:13 2006 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,262 +0,0 @@ -/* -*- C++ -*- - * - * This file is a part of LEMON, a generic C++ optimization library - * - * Copyright (C) 2003-2006 - * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport - * (Egervary Research Group on Combinatorial Optimization, EGRES). - * - * Permission to use, modify and distribute this software is granted - * provided that this copyright notice appears in all copies. For - * precise terms see the accompanying LICENSE file. - * - * This software is provided "AS IS" with no warranty of any kind, - * express or implied, and with no claim as to its suitability for any - * purpose. - * - */ - -#ifndef LEMON_MIN_COST_FLOW_H -#define LEMON_MIN_COST_FLOW_H - -///\ingroup flowalgs -///\file -///\brief An algorithm for finding a flow of value \c k (for small values of \c k) having minimal total cost - - -#include -#include -#include -#include - -namespace lemon { - -/// \addtogroup flowalgs -/// @{ - - ///\brief Implementation of an algorithm for finding a flow of value \c k - ///(for small values of \c k) having minimal total cost between 2 nodes - /// - /// - /// The class \ref lemon::MinCostFlow "MinCostFlow" implements an - /// algorithm for finding a flow of value \c k having minimal total - /// cost from a given source node to a given target node in a - /// directed graph with a cost function on the edges. To - /// this end, the edge-capacities and edge-costs have to be - /// nonnegative. The edge-capacities should be integers, but the - /// edge-costs can be integers, reals or of other comparable - /// numeric type. This algorithm is intended to be used only for - /// small values of \c k, since it is only polynomial in k, not in - /// the length of k (which is log k): in order to find the minimum - /// cost flow of value \c k it finds the minimum cost flow of value - /// \c i for every \c i between 0 and \c k. - /// - ///\param Graph The directed graph type the algorithm runs on. - ///\param LengthMap The type of the length map. - ///\param CapacityMap The capacity map type. - /// - ///\author Attila Bernath - template - class MinCostFlow { - - typedef typename LengthMap::Value Length; - - //Warning: this should be integer type - typedef typename CapacityMap::Value Capacity; - - typedef typename Graph::Node Node; - typedef typename Graph::NodeIt NodeIt; - typedef typename Graph::Edge Edge; - typedef typename Graph::OutEdgeIt OutEdgeIt; - typedef typename Graph::template EdgeMap EdgeIntMap; - - typedef ResGraphAdaptor ResGW; - typedef typename ResGW::Edge ResGraphEdge; - - protected: - - const Graph& g; - const LengthMap& length; - const CapacityMap& capacity; - - EdgeIntMap flow; - typedef typename Graph::template NodeMap PotentialMap; - PotentialMap potential; - - Node s; - Node t; - - Length total_length; - - class ModLengthMap { - typedef typename Graph::template NodeMap NodeMap; - const ResGW& g; - const LengthMap &length; - const NodeMap &pot; - public : - typedef typename LengthMap::Key Key; - typedef typename LengthMap::Value Value; - - ModLengthMap(const ResGW& _g, - const LengthMap &_length, const NodeMap &_pot) : - g(_g), /*rev(_rev),*/ length(_length), pot(_pot) { } - - Value operator[](typename ResGW::Edge e) const { - if (g.forward(e)) - return length[e]-(pot[g.target(e)]-pot[g.source(e)]); - else - return -length[e]-(pot[g.target(e)]-pot[g.source(e)]); - } - - }; //ModLengthMap - - ResGW res_graph; - ModLengthMap mod_length; - Dijkstra dijkstra; - - public : - - /*! \brief The constructor of the class. - - \param _g The directed graph the algorithm runs on. - \param _length The length (cost) of the edges. - \param _cap The capacity of the edges. - \param _s Source node. - \param _t Target node. - */ - MinCostFlow(Graph& _g, LengthMap& _length, CapacityMap& _cap, - Node _s, Node _t) : - g(_g), length(_length), capacity(_cap), flow(_g), potential(_g), - s(_s), t(_t), - res_graph(g, capacity, flow), - mod_length(res_graph, length, potential), - dijkstra(res_graph, mod_length) { - reset(); - } - - /*! Tries to augment the flow between s and t by 1. - The return value shows if the augmentation is successful. - */ - bool augment() { - dijkstra.run(s); - if (!dijkstra.reached(t)) { - - //Unsuccessful augmentation. - return false; - } else { - - //We have to change the potential - for(typename ResGW::NodeIt n(res_graph); n!=INVALID; ++n) - potential.set(n, potential[n]+dijkstra.distMap()[n]); - - //Augmenting on the shortest path - Node n=t; - ResGraphEdge e; - while (n!=s){ - e = dijkstra.predEdge(n); - n = dijkstra.predNode(n); - res_graph.augment(e,1); - //Let's update the total length - if (res_graph.forward(e)) - total_length += length[e]; - else - total_length -= length[e]; - } - - return true; - } - } - - /*! \brief Runs the algorithm. - - Runs the algorithm. - Returns k if there is a flow of value at least k from s to t. - Otherwise it returns the maximum value of a flow from s to t. - - \param k The value of the flow we are looking for. - - \todo May be it does make sense to be able to start with a nonzero - feasible primal-dual solution pair as well. - - \todo If the actual flow value is bigger than k, then everything is - cleared and the algorithm starts from zero flow. Is it a good approach? - */ - int run(int k) { - if (flowValue()>k) reset(); - while (flowValue() 0 && fl_e != 0) - return false; - if (mod_pot < 0 && fl_e != capacity[e]) - return false; - } - } - return true; - } - - }; //class MinCostFlow - - ///@} - -} //namespace lemon - -#endif //LEMON_MIN_COST_FLOW_H diff -r ff46747676ed -r 1a8a66b6c6ce lemon/ssp_min_cost_flow.h --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/lemon/ssp_min_cost_flow.h Mon Oct 30 17:22:14 2006 +0000 @@ -0,0 +1,260 @@ +/* -*- C++ -*- + * + * This file is a part of LEMON, a generic C++ optimization library + * + * Copyright (C) 2003-2006 + * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport + * (Egervary Research Group on Combinatorial Optimization, EGRES). + * + * Permission to use, modify and distribute this software is granted + * provided that this copyright notice appears in all copies. For + * precise terms see the accompanying LICENSE file. + * + * This software is provided "AS IS" with no warranty of any kind, + * express or implied, and with no claim as to its suitability for any + * purpose. + * + */ + +#ifndef LEMON_MIN_COST_FLOW_H +#define LEMON_MIN_COST_FLOW_H + +///\ingroup flowalgs +/// +///\file \brief An algorithm for finding a flow of value \c k (for +///small values of \c k) having minimal total cost + + +#include +#include +#include +#include + +namespace lemon { + + /// \addtogroup flowalgs + /// @{ + + /// \brief Implementation of an algorithm for finding a flow of + /// value \c k (for small values of \c k) having minimal total cost + /// between two nodes + /// + /// + /// The \ref lemon::SspMinCostFlow "Successive Shortest Path Minimum + /// Cost Flow" implements an algorithm for finding a flow of value + /// \c k having minimal total cost from a given source node to a + /// given target node in a directed graph with a cost function on + /// the edges. To this end, the edge-capacities and edge-costs have + /// to be nonnegative. The edge-capacities should be integers, but + /// the edge-costs can be integers, reals or of other comparable + /// numeric type. This algorithm is intended to be used only for + /// small values of \c k, since it is only polynomial in k, not in + /// the length of k (which is log k): in order to find the minimum + /// cost flow of value \c k it finds the minimum cost flow of value + /// \c i for every \c i between 0 and \c k. + /// + ///\param Graph The directed graph type the algorithm runs on. + ///\param LengthMap The type of the length map. + ///\param CapacityMap The capacity map type. + /// + ///\author Attila Bernath + template + class SspMinCostFlow { + + typedef typename LengthMap::Value Length; + + //Warning: this should be integer type + typedef typename CapacityMap::Value Capacity; + + typedef typename Graph::Node Node; + typedef typename Graph::NodeIt NodeIt; + typedef typename Graph::Edge Edge; + typedef typename Graph::OutEdgeIt OutEdgeIt; + typedef typename Graph::template EdgeMap EdgeIntMap; + + typedef ResGraphAdaptor ResGW; + typedef typename ResGW::Edge ResGraphEdge; + + protected: + + const Graph& g; + const LengthMap& length; + const CapacityMap& capacity; + + EdgeIntMap flow; + typedef typename Graph::template NodeMap PotentialMap; + PotentialMap potential; + + Node s; + Node t; + + Length total_length; + + class ModLengthMap { + typedef typename Graph::template NodeMap NodeMap; + const ResGW& g; + const LengthMap &length; + const NodeMap &pot; + public : + typedef typename LengthMap::Key Key; + typedef typename LengthMap::Value Value; + + ModLengthMap(const ResGW& _g, + const LengthMap &_length, const NodeMap &_pot) : + g(_g), /*rev(_rev),*/ length(_length), pot(_pot) { } + + Value operator[](typename ResGW::Edge e) const { + if (g.forward(e)) + return length[e]-(pot[g.target(e)]-pot[g.source(e)]); + else + return -length[e]-(pot[g.target(e)]-pot[g.source(e)]); + } + + }; //ModLengthMap + + ResGW res_graph; + ModLengthMap mod_length; + Dijkstra dijkstra; + + public : + + /// \brief The constructor of the class. + /// + /// \param _g The directed graph the algorithm runs on. + /// \param _length The length (cost) of the edges. + /// \param _cap The capacity of the edges. + /// \param _s Source node. + /// \param _t Target node. + SspMinCostFlow(Graph& _g, LengthMap& _length, CapacityMap& _cap, + Node _s, Node _t) : + g(_g), length(_length), capacity(_cap), flow(_g), potential(_g), + s(_s), t(_t), + res_graph(g, capacity, flow), + mod_length(res_graph, length, potential), + dijkstra(res_graph, mod_length) { + reset(); + } + + /// \brief Tries to augment the flow between s and t by 1. The + /// return value shows if the augmentation is successful. + bool augment() { + dijkstra.run(s); + if (!dijkstra.reached(t)) { + + //Unsuccessful augmentation. + return false; + } else { + + //We have to change the potential + for(typename ResGW::NodeIt n(res_graph); n!=INVALID; ++n) + potential.set(n, potential[n]+dijkstra.distMap()[n]); + + //Augmenting on the shortest path + Node n=t; + ResGraphEdge e; + while (n!=s){ + e = dijkstra.predEdge(n); + n = dijkstra.predNode(n); + res_graph.augment(e,1); + //Let's update the total length + if (res_graph.forward(e)) + total_length += length[e]; + else + total_length -= length[e]; + } + + return true; + } + } + + /// \brief Runs the algorithm. + /// + /// Runs the algorithm. + /// Returns k if there is a flow of value at least k from s to t. + /// Otherwise it returns the maximum value of a flow from s to t. + /// + /// \param k The value of the flow we are looking for. + /// + /// \todo May be it does make sense to be able to start with a + /// nonzero feasible primal-dual solution pair as well. + /// + /// \todo If the actual flow value is bigger than k, then + /// everything is cleared and the algorithm starts from zero + /// flow. Is it a good approach? + int run(int k) { + if (flowValue()>k) reset(); + while (flowValue() 0 && fl_e != 0) + return false; + if (mod_pot < 0 && fl_e != capacity[e]) + return false; + } + } + return true; + } + + }; //class SspMinCostFlow + + ///@} + +} //namespace lemon + +#endif //LEMON_MIN_COST_FLOW_H diff -r ff46747676ed -r 1a8a66b6c6ce lemon/suurballe.h --- a/lemon/suurballe.h Mon Oct 30 16:26:13 2006 +0000 +++ b/lemon/suurballe.h Mon Oct 30 17:22:14 2006 +0000 @@ -26,15 +26,15 @@ #include #include -#include +#include namespace lemon { /// \addtogroup flowalgs /// @{ - ///\brief Implementation of an algorithm for finding k edge-disjoint paths between 2 nodes - /// of minimal total length + ///\brief Implementation of an algorithm for finding k edge-disjoint + /// paths between 2 nodes of minimal total length /// /// The class \ref lemon::Suurballe implements /// an algorithm for finding k edge-disjoint paths @@ -49,7 +49,7 @@ ///\note It it questionable whether it is correct to call this method after ///%Suurballe for it is just a special case of Edmonds' and Karp's algorithm ///for finding minimum cost flows. In fact, this implementation just - ///wraps the MinCostFlow algorithms. The paper of both %Suurballe and + ///wraps the SspMinCostFlow algorithms. The paper of both %Suurballe and ///Edmonds-Karp published in 1972, therefore it is possibly right to ///state that they are ///independent results. Most frequently this special case is referred as @@ -79,7 +79,7 @@ //This is the capacity map for the mincostflow problem ConstMap const1map; //This MinCostFlow instance will actually solve the problem - MinCostFlow min_cost_flow; + SspMinCostFlow min_cost_flow; //Container to store found paths std::vector< std::vector > paths; @@ -87,25 +87,24 @@ public : - /*! \brief The constructor of the class. - - \param _G The directed graph the algorithm runs on. - \param _length The length (weight or cost) of the edges. - \param _s Source node. - \param _t Target node. - */ + /// \brief The constructor of the class. + /// + /// \param _G The directed graph the algorithm runs on. + /// \param _length The length (weight or cost) of the edges. + /// \param _s Source node. + /// \param _t Target node. Suurballe(Graph& _G, LengthMap& _length, Node _s, Node _t) : G(_G), s(_s), t(_t), const1map(1), min_cost_flow(_G, _length, const1map, _s, _t) { } - ///Runs the algorithm. - - ///Runs the algorithm. - ///Returns k if there are at least k edge-disjoint paths from s to t. - ///Otherwise it returns the number of edge-disjoint paths found - ///from s to t. + /// \brief Runs the algorithm. /// - ///\param k How many paths are we looking for? + /// Runs the algorithm. + /// Returns k if there are at least k edge-disjoint paths from s to t. + /// Otherwise it returns the number of edge-disjoint paths found + /// from s to t. + /// + /// \param k How many paths are we looking for? /// int run(int k) { int i = min_cost_flow.run(k); @@ -144,46 +143,49 @@ } - ///Returns the total length of the paths. - - ///This function gives back the total length of the found paths. + /// \brief Returns the total length of the paths. + /// + /// This function gives back the total length of the found paths. Length totalLength(){ return min_cost_flow.totalLength(); } - ///Returns the found flow. - - ///This function returns a const reference to the EdgeMap \c flow. + /// \brief Returns the found flow. + /// + /// This function returns a const reference to the EdgeMap \c flow. const EdgeIntMap &getFlow() const { return min_cost_flow.flow;} - /// Returns the optimal dual solution - - ///This function returns a const reference to the NodeMap - ///\c potential (the dual solution). + /// \brief Returns the optimal dual solution + /// + /// This function returns a const reference to the NodeMap \c + /// potential (the dual solution). const EdgeIntMap &getPotential() const { return min_cost_flow.potential;} - ///Checks whether the complementary slackness holds. - - ///This function checks, whether the given solution is optimal. - ///Currently this function only checks optimality, - ///doesn't bother with feasibility. - ///It is meant for testing purposes. + /// \brief Checks whether the complementary slackness holds. + /// + /// This function checks, whether the given solution is optimal. + /// Currently this function only checks optimality, doesn't bother + /// with feasibility. It is meant for testing purposes. bool checkComplementarySlackness(){ return min_cost_flow.checkComplementarySlackness(); } - ///Read the found paths. - - ///This function gives back the \c j-th path in argument p. - ///Assumes that \c run() has been run and nothing has changed since then. - /// \warning It is assumed that \c p is constructed to - ///be a path of graph \c G. - ///If \c j is not less than the result of previous \c run, - ///then the result here will be an empty path (\c j can be 0 as well). + /// \brief Read the found paths. /// - ///\param Path The type of the path structure to put the result to (must meet lemon path concept). - ///\param p The path to put the result to. - ///\param j Which path you want to get from the found paths (in a real application you would get the found paths iteratively). + /// This function gives back the \c j-th path in argument p. + /// Assumes that \c run() has been run and nothing has changed + /// since then. + /// + /// \warning It is assumed that \c p is constructed to be a path + /// of graph \c G. If \c j is not less than the result of + /// previous \c run, then the result here will be an empty path + /// (\c j can be 0 as well). + /// + /// \param Path The type of the path structure to put the result + /// to (must meet lemon path concept). + /// \param p The path to put the result to. + /// \param j Which path you want to get from the found paths (in a + /// real application you would get the found paths iteratively). template void getPath(Path& p, size_t j){ diff -r ff46747676ed -r 1a8a66b6c6ce test/min_cost_flow_test.cc --- a/test/min_cost_flow_test.cc Mon Oct 30 16:26:13 2006 +0000 +++ b/test/min_cost_flow_test.cc Mon Oct 30 17:22:14 2006 +0000 @@ -19,7 +19,7 @@ #include #include "test_tools.h" #include -#include +#include //#include //#include @@ -92,7 +92,7 @@ // ConstMap const1map(1); std::cout << "Mincostflows algorithm test..." << std::endl; - MinCostFlow< Graph, Graph::EdgeMap, Graph::EdgeMap > + SspMinCostFlow< Graph, Graph::EdgeMap, Graph::EdgeMap > surb_test(graph, length, capacity, s, t); int k=1;