/* -*- C++ -*- * src/lemon/suurballe.h - Part of LEMON, a generic C++ optimization library * * Copyright (C) 2004 Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport * (Egervary Combinatorial Optimization Research Group, 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_SUURBALLE_H #define LEMON_SUURBALLE_H ///\ingroup flowalgs ///\file ///\brief An algorithm for finding k paths of minimal total length. #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 /// /// The class \ref lemon::Suurballe implements /// an algorithm for finding k edge-disjoint paths /// from a given source node to a given target node in an /// edge-weighted directed graph having minimal total weight (length). /// ///\warning Length values should be nonnegative. /// ///\param Graph The directed graph type the algorithm runs on. ///\param LengthMap The type of the length map (values should be nonnegative). /// ///\note It it questionable whether it is correct to call this method after ///%Suurballe for it is just a special case of Edmond's and Karp's algorithm ///for finding minimum cost flows. In fact, this implementation just ///wraps the MinCostFlow 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 ///%Suurballe method in the literature, especially in communication ///network context. ///\author Attila Bernath template class Suurballe{ typedef typename LengthMap::Value Length; 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 ConstMap ConstMap; const Graph& G; Node s; Node t; //Auxiliary variables //This is the capacity map for the mincostflow problem ConstMap const1map; //This MinCostFlow instance will actually solve the problem MinCostFlow min_cost_flow; //Container to store found paths std::vector< std::vector > paths; 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. */ 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. /// ///\param k How many paths are we looking for? /// int run(int k) { int i = min_cost_flow.run(k); //Let's find the paths //We put the paths into stl vectors (as an inner representation). //In the meantime we lose the information stored in 'reversed'. //We suppose the lengths to be positive now. //We don't want to change the flow of min_cost_flow, so we make a copy //The name here suggests that the flow has only 0/1 values. EdgeIntMap reversed(G); for(typename Graph::EdgeIt e(G); e!=INVALID; ++e) reversed[e] = min_cost_flow.getFlow()[e]; paths.clear(); //total_length=0; paths.resize(k); for (int j=0; j void getPath(Path& p, size_t j){ p.clear(); if (j>paths.size()-1){ return; } typename Path::Builder B(p); for(typename std::vector::iterator i=paths[j].begin(); i!=paths[j].end(); ++i ){ B.pushBack(*i); } B.commit(); } }; //class Suurballe ///@} } //namespace lemon #endif //LEMON_SUURBALLE_H