/* -*- C++ -*- * * This file is a part of LEMON, a generic C++ optimization library * * Copyright (C) 2003-2008 * 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_KARP_H #define LEMON_KARP_H /// \ingroup shortest_path /// /// \file /// \brief Karp's algorithm for finding a minimum mean cycle. #include #include #include #include #include #include namespace lemon { /// \brief Default traits class of Karp algorithm. /// /// Default traits class of Karp algorithm. /// \tparam GR The type of the digraph. /// \tparam LEN The type of the length map. /// It must conform to the \ref concepts::ReadMap "ReadMap" concept. #ifdef DOXYGEN template #else template ::is_integer> #endif struct KarpDefaultTraits { /// The type of the digraph typedef GR Digraph; /// The type of the length map typedef LEN LengthMap; /// The type of the arc lengths typedef typename LengthMap::Value Value; /// \brief The large value type used for internal computations /// /// The large value type used for internal computations. /// It is \c long \c long if the \c Value type is integer, /// otherwise it is \c double. /// \c Value must be convertible to \c LargeValue. typedef double LargeValue; /// The tolerance type used for internal computations typedef lemon::Tolerance Tolerance; /// \brief The path type of the found cycles /// /// The path type of the found cycles. /// It must conform to the \ref lemon::concepts::Path "Path" concept /// and it must have an \c addBack() function. typedef lemon::Path Path; }; // Default traits class for integer value types template struct KarpDefaultTraits { typedef GR Digraph; typedef LEN LengthMap; typedef typename LengthMap::Value Value; #ifdef LEMON_HAVE_LONG_LONG typedef long long LargeValue; #else typedef long LargeValue; #endif typedef lemon::Tolerance Tolerance; typedef lemon::Path Path; }; /// \addtogroup shortest_path /// @{ /// \brief Implementation of Karp's algorithm for finding a minimum /// mean cycle. /// /// This class implements Karp's algorithm for finding a directed /// cycle of minimum mean length (cost) in a digraph. /// /// \tparam GR The type of the digraph the algorithm runs on. /// \tparam LEN The type of the length map. The default /// map type is \ref concepts::Digraph::ArcMap "GR::ArcMap". #ifdef DOXYGEN template #else template < typename GR, typename LEN = typename GR::template ArcMap, typename TR = KarpDefaultTraits > #endif class Karp { public: /// The type of the digraph typedef typename TR::Digraph Digraph; /// The type of the length map typedef typename TR::LengthMap LengthMap; /// The type of the arc lengths typedef typename TR::Value Value; /// \brief The large value type /// /// The large value type used for internal computations. /// Using the \ref KarpDefaultTraits "default traits class", /// it is \c long \c long if the \c Value type is integer, /// otherwise it is \c double. typedef typename TR::LargeValue LargeValue; /// The tolerance type typedef typename TR::Tolerance Tolerance; /// \brief The path type of the found cycles /// /// The path type of the found cycles. /// Using the \ref KarpDefaultTraits "default traits class", /// it is \ref lemon::Path "Path". typedef typename TR::Path Path; /// The \ref KarpDefaultTraits "traits class" of the algorithm typedef TR Traits; private: TEMPLATE_DIGRAPH_TYPEDEFS(Digraph); // Data sturcture for path data struct PathData { bool found; LargeValue dist; Arc pred; PathData(bool f = false, LargeValue d = 0, Arc p = INVALID) : found(f), dist(d), pred(p) {} }; typedef typename Digraph::template NodeMap > PathDataNodeMap; private: // The digraph the algorithm runs on const Digraph &_gr; // The length of the arcs const LengthMap &_length; // Data for storing the strongly connected components int _comp_num; typename Digraph::template NodeMap _comp; std::vector > _comp_nodes; std::vector* _nodes; typename Digraph::template NodeMap > _out_arcs; // Data for the found cycle LargeValue _cycle_length; int _cycle_size; Node _cycle_node; Path *_cycle_path; bool _local_path; // Node map for storing path data PathDataNodeMap _data; // The processed nodes in the last round std::vector _process; Tolerance _tolerance; public: /// \name Named Template Parameters /// @{ template struct SetLargeValueTraits : public Traits { typedef T LargeValue; typedef lemon::Tolerance Tolerance; }; /// \brief \ref named-templ-param "Named parameter" for setting /// \c LargeValue type. /// /// \ref named-templ-param "Named parameter" for setting \c LargeValue /// type. It is used for internal computations in the algorithm. template struct SetLargeValue : public Karp > { typedef Karp > Create; }; template struct SetPathTraits : public Traits { typedef T Path; }; /// \brief \ref named-templ-param "Named parameter" for setting /// \c %Path type. /// /// \ref named-templ-param "Named parameter" for setting the \c %Path /// type of the found cycles. /// It must conform to the \ref lemon::concepts::Path "Path" concept /// and it must have an \c addFront() function. template struct SetPath : public Karp > { typedef Karp > Create; }; /// @} public: /// \brief Constructor. /// /// The constructor of the class. /// /// \param digraph The digraph the algorithm runs on. /// \param length The lengths (costs) of the arcs. Karp( const Digraph &digraph, const LengthMap &length ) : _gr(digraph), _length(length), _comp(digraph), _out_arcs(digraph), _cycle_length(0), _cycle_size(1), _cycle_node(INVALID), _cycle_path(NULL), _local_path(false), _data(digraph) {} /// Destructor. ~Karp() { if (_local_path) delete _cycle_path; } /// \brief Set the path structure for storing the found cycle. /// /// This function sets an external path structure for storing the /// found cycle. /// /// If you don't call this function before calling \ref run() or /// \ref findMinMean(), it will allocate a local \ref Path "path" /// structure. The destuctor deallocates this automatically /// allocated object, of course. /// /// \note The algorithm calls only the \ref lemon::Path::addFront() /// "addFront()" function of the given path structure. /// /// \return (*this) Karp& cycle(Path &path) { if (_local_path) { delete _cycle_path; _local_path = false; } _cycle_path = &path; return *this; } /// \name Execution control /// The simplest way to execute the algorithm is to call the \ref run() /// function.\n /// If you only need the minimum mean length, you may call /// \ref findMinMean(). /// @{ /// \brief Run the algorithm. /// /// This function runs the algorithm. /// It can be called more than once (e.g. if the underlying digraph /// and/or the arc lengths have been modified). /// /// \return \c true if a directed cycle exists in the digraph. /// /// \note mmc.run() is just a shortcut of the following code. /// \code /// return mmc.findMinMean() && mmc.findCycle(); /// \endcode bool run() { return findMinMean() && findCycle(); } /// \brief Find the minimum cycle mean. /// /// This function finds the minimum mean length of the directed /// cycles in the digraph. /// /// \return \c true if a directed cycle exists in the digraph. bool findMinMean() { // Initialization and find strongly connected components init(); findComponents(); // Find the minimum cycle mean in the components for (int comp = 0; comp < _comp_num; ++comp) { if (!initComponent(comp)) continue; processRounds(); updateMinMean(); } return (_cycle_node != INVALID); } /// \brief Find a minimum mean directed cycle. /// /// This function finds a directed cycle of minimum mean length /// in the digraph using the data computed by findMinMean(). /// /// \return \c true if a directed cycle exists in the digraph. /// /// \pre \ref findMinMean() must be called before using this function. bool findCycle() { if (_cycle_node == INVALID) return false; IntNodeMap reached(_gr, -1); int r = _data[_cycle_node].size(); Node u = _cycle_node; while (reached[u] < 0) { reached[u] = --r; u = _gr.source(_data[u][r].pred); } r = reached[u]; Arc e = _data[u][r].pred; _cycle_path->addFront(e); _cycle_length = _length[e]; _cycle_size = 1; Node v; while ((v = _gr.source(e)) != u) { e = _data[v][--r].pred; _cycle_path->addFront(e); _cycle_length += _length[e]; ++_cycle_size; } return true; } /// @} /// \name Query Functions /// The results of the algorithm can be obtained using these /// functions.\n /// The algorithm should be executed before using them. /// @{ /// \brief Return the total length of the found cycle. /// /// This function returns the total length of the found cycle. /// /// \pre \ref run() or \ref findMinMean() must be called before /// using this function. LargeValue cycleLength() const { return _cycle_length; } /// \brief Return the number of arcs on the found cycle. /// /// This function returns the number of arcs on the found cycle. /// /// \pre \ref run() or \ref findMinMean() must be called before /// using this function. int cycleArcNum() const { return _cycle_size; } /// \brief Return the mean length of the found cycle. /// /// This function returns the mean length of the found cycle. /// /// \note alg.cycleMean() is just a shortcut of the /// following code. /// \code /// return static_cast(alg.cycleLength()) / alg.cycleArcNum(); /// \endcode /// /// \pre \ref run() or \ref findMinMean() must be called before /// using this function. double cycleMean() const { return static_cast(_cycle_length) / _cycle_size; } /// \brief Return the found cycle. /// /// This function returns a const reference to the path structure /// storing the found cycle. /// /// \pre \ref run() or \ref findCycle() must be called before using /// this function. const Path& cycle() const { return *_cycle_path; } ///@} private: // Initialization void init() { if (!_cycle_path) { _local_path = true; _cycle_path = new Path; } _cycle_path->clear(); _cycle_length = 0; _cycle_size = 1; _cycle_node = INVALID; for (NodeIt u(_gr); u != INVALID; ++u) _data[u].clear(); } // Find strongly connected components and initialize _comp_nodes // and _out_arcs void findComponents() { _comp_num = stronglyConnectedComponents(_gr, _comp); _comp_nodes.resize(_comp_num); if (_comp_num == 1) { _comp_nodes[0].clear(); for (NodeIt n(_gr); n != INVALID; ++n) { _comp_nodes[0].push_back(n); _out_arcs[n].clear(); for (OutArcIt a(_gr, n); a != INVALID; ++a) { _out_arcs[n].push_back(a); } } } else { for (int i = 0; i < _comp_num; ++i) _comp_nodes[i].clear(); for (NodeIt n(_gr); n != INVALID; ++n) { int k = _comp[n]; _comp_nodes[k].push_back(n); _out_arcs[n].clear(); for (OutArcIt a(_gr, n); a != INVALID; ++a) { if (_comp[_gr.target(a)] == k) _out_arcs[n].push_back(a); } } } } // Initialize path data for the current component bool initComponent(int comp) { _nodes = &(_comp_nodes[comp]); int n = _nodes->size(); if (n < 1 || (n == 1 && _out_arcs[(*_nodes)[0]].size() == 0)) { return false; } for (int i = 0; i < n; ++i) { _data[(*_nodes)[i]].resize(n + 1); } return true; } // Process all rounds of computing path data for the current component. // _data[v][k] is the length of a shortest directed walk from the root // node to node v containing exactly k arcs. void processRounds() { Node start = (*_nodes)[0]; _data[start][0] = PathData(true, 0); _process.clear(); _process.push_back(start); int k, n = _nodes->size(); for (k = 1; k <= n && int(_process.size()) < n; ++k) { processNextBuildRound(k); } for ( ; k <= n; ++k) { processNextFullRound(k); } } // Process one round and rebuild _process void processNextBuildRound(int k) { std::vector next; Node u, v; Arc e; LargeValue d; for (int i = 0; i < int(_process.size()); ++i) { u = _process[i]; for (int j = 0; j < int(_out_arcs[u].size()); ++j) { e = _out_arcs[u][j]; v = _gr.target(e); d = _data[u][k-1].dist + _length[e]; if (!_data[v][k].found) { next.push_back(v); _data[v][k] = PathData(true, _data[u][k-1].dist + _length[e], e); } else if (_tolerance.less(d, _data[v][k].dist)) { _data[v][k] = PathData(true, d, e); } } } _process.swap(next); } // Process one round using _nodes instead of _process void processNextFullRound(int k) { Node u, v; Arc e; LargeValue d; for (int i = 0; i < int(_nodes->size()); ++i) { u = (*_nodes)[i]; for (int j = 0; j < int(_out_arcs[u].size()); ++j) { e = _out_arcs[u][j]; v = _gr.target(e); d = _data[u][k-1].dist + _length[e]; if (!_data[v][k].found || _tolerance.less(d, _data[v][k].dist)) { _data[v][k] = PathData(true, d, e); } } } } // Update the minimum cycle mean void updateMinMean() { int n = _nodes->size(); for (int i = 0; i < n; ++i) { Node u = (*_nodes)[i]; if (!_data[u][n].found) continue; LargeValue length, max_length = 0; int size, max_size = 1; bool found_curr = false; for (int k = 0; k < n; ++k) { if (!_data[u][k].found) continue; length = _data[u][n].dist - _data[u][k].dist; size = n - k; if (!found_curr || length * max_size > max_length * size) { found_curr = true; max_length = length; max_size = size; } } if ( found_curr && (_cycle_node == INVALID || max_length * _cycle_size < _cycle_length * max_size) ) { _cycle_length = max_length; _cycle_size = max_size; _cycle_node = u; } } } }; //class Karp ///@} } //namespace lemon #endif //LEMON_KARP_H