alpar@877: /* -*- mode: C++; indent-tabs-mode: nil; -*-
kpeter@766: *
alpar@877: * This file is a part of LEMON, a generic C++ optimization library.
kpeter@766: *
alpar@877: * Copyright (C) 2003-2010
kpeter@766: * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
kpeter@766: * (Egervary Research Group on Combinatorial Optimization, EGRES).
kpeter@766: *
kpeter@766: * Permission to use, modify and distribute this software is granted
kpeter@766: * provided that this copyright notice appears in all copies. For
kpeter@766: * precise terms see the accompanying LICENSE file.
kpeter@766: *
kpeter@766: * This software is provided "AS IS" with no warranty of any kind,
kpeter@766: * express or implied, and with no claim as to its suitability for any
kpeter@766: * purpose.
kpeter@766: *
kpeter@766: */
kpeter@766:
kpeter@864: #ifndef LEMON_HARTMANN_ORLIN_MMC_H
kpeter@864: #define LEMON_HARTMANN_ORLIN_MMC_H
kpeter@766:
kpeter@768: /// \ingroup min_mean_cycle
kpeter@766: ///
kpeter@766: /// \file
kpeter@766: /// \brief Hartmann-Orlin's algorithm for finding a minimum mean cycle.
kpeter@766:
kpeter@766: #include <vector>
kpeter@766: #include <limits>
kpeter@766: #include <lemon/core.h>
kpeter@766: #include <lemon/path.h>
kpeter@766: #include <lemon/tolerance.h>
kpeter@766: #include <lemon/connectivity.h>
kpeter@766:
kpeter@766: namespace lemon {
kpeter@766:
kpeter@864: /// \brief Default traits class of HartmannOrlinMmc class.
kpeter@766: ///
kpeter@864: /// Default traits class of HartmannOrlinMmc class.
kpeter@766: /// \tparam GR The type of the digraph.
kpeter@864: /// \tparam CM The type of the cost map.
kpeter@879: /// It must conform to the \ref concepts::ReadMap "ReadMap" concept.
kpeter@766: #ifdef DOXYGEN
kpeter@864: template <typename GR, typename CM>
kpeter@766: #else
kpeter@864: template <typename GR, typename CM,
kpeter@864: bool integer = std::numeric_limits<typename CM::Value>::is_integer>
kpeter@766: #endif
kpeter@864: struct HartmannOrlinMmcDefaultTraits
kpeter@766: {
kpeter@766: /// The type of the digraph
kpeter@766: typedef GR Digraph;
kpeter@864: /// The type of the cost map
kpeter@864: typedef CM CostMap;
kpeter@864: /// The type of the arc costs
kpeter@864: typedef typename CostMap::Value Cost;
kpeter@766:
kpeter@864: /// \brief The large cost type used for internal computations
kpeter@766: ///
kpeter@864: /// The large cost type used for internal computations.
kpeter@864: /// It is \c long \c long if the \c Cost type is integer,
kpeter@766: /// otherwise it is \c double.
kpeter@864: /// \c Cost must be convertible to \c LargeCost.
kpeter@864: typedef double LargeCost;
kpeter@766:
kpeter@766: /// The tolerance type used for internal computations
kpeter@864: typedef lemon::Tolerance<LargeCost> Tolerance;
kpeter@766:
kpeter@766: /// \brief The path type of the found cycles
kpeter@766: ///
kpeter@766: /// The path type of the found cycles.
kpeter@766: /// It must conform to the \ref lemon::concepts::Path "Path" concept
kpeter@772: /// and it must have an \c addFront() function.
kpeter@766: typedef lemon::Path<Digraph> Path;
kpeter@766: };
kpeter@766:
kpeter@864: // Default traits class for integer cost types
kpeter@864: template <typename GR, typename CM>
kpeter@864: struct HartmannOrlinMmcDefaultTraits<GR, CM, true>
kpeter@766: {
kpeter@766: typedef GR Digraph;
kpeter@864: typedef CM CostMap;
kpeter@864: typedef typename CostMap::Value Cost;
kpeter@766: #ifdef LEMON_HAVE_LONG_LONG
kpeter@864: typedef long long LargeCost;
kpeter@766: #else
kpeter@864: typedef long LargeCost;
kpeter@766: #endif
kpeter@864: typedef lemon::Tolerance<LargeCost> Tolerance;
kpeter@766: typedef lemon::Path<Digraph> Path;
kpeter@766: };
kpeter@766:
kpeter@766:
kpeter@768: /// \addtogroup min_mean_cycle
kpeter@766: /// @{
kpeter@766:
kpeter@766: /// \brief Implementation of the Hartmann-Orlin algorithm for finding
kpeter@766: /// a minimum mean cycle.
kpeter@766: ///
kpeter@766: /// This class implements the Hartmann-Orlin algorithm for finding
kpeter@864: /// a directed cycle of minimum mean cost in a digraph
kpeter@771: /// \ref amo93networkflows, \ref dasdan98minmeancycle.
kpeter@879: /// It is an improved version of \ref KarpMmc "Karp"'s original algorithm,
kpeter@766: /// it applies an efficient early termination scheme.
kpeter@768: /// It runs in time O(ne) and uses space O(n<sup>2</sup>+e).
kpeter@766: ///
kpeter@766: /// \tparam GR The type of the digraph the algorithm runs on.
kpeter@864: /// \tparam CM The type of the cost map. The default
kpeter@766: /// map type is \ref concepts::Digraph::ArcMap "GR::ArcMap<int>".
kpeter@825: /// \tparam TR The traits class that defines various types used by the
kpeter@864: /// algorithm. By default, it is \ref HartmannOrlinMmcDefaultTraits
kpeter@864: /// "HartmannOrlinMmcDefaultTraits<GR, CM>".
kpeter@825: /// In most cases, this parameter should not be set directly,
kpeter@825: /// consider to use the named template parameters instead.
kpeter@766: #ifdef DOXYGEN
kpeter@864: template <typename GR, typename CM, typename TR>
kpeter@766: #else
kpeter@766: template < typename GR,
kpeter@864: typename CM = typename GR::template ArcMap<int>,
kpeter@864: typename TR = HartmannOrlinMmcDefaultTraits<GR, CM> >
kpeter@766: #endif
kpeter@864: class HartmannOrlinMmc
kpeter@766: {
kpeter@766: public:
kpeter@766:
kpeter@766: /// The type of the digraph
kpeter@766: typedef typename TR::Digraph Digraph;
kpeter@864: /// The type of the cost map
kpeter@864: typedef typename TR::CostMap CostMap;
kpeter@864: /// The type of the arc costs
kpeter@864: typedef typename TR::Cost Cost;
kpeter@766:
kpeter@864: /// \brief The large cost type
kpeter@766: ///
kpeter@864: /// The large cost type used for internal computations.
kpeter@864: /// By default, it is \c long \c long if the \c Cost type is integer,
kpeter@766: /// otherwise it is \c double.
kpeter@864: typedef typename TR::LargeCost LargeCost;
kpeter@766:
kpeter@766: /// The tolerance type
kpeter@766: typedef typename TR::Tolerance Tolerance;
kpeter@766:
kpeter@766: /// \brief The path type of the found cycles
kpeter@766: ///
kpeter@766: /// The path type of the found cycles.
kpeter@864: /// Using the \ref HartmannOrlinMmcDefaultTraits "default traits class",
kpeter@766: /// it is \ref lemon::Path "Path<Digraph>".
kpeter@766: typedef typename TR::Path Path;
kpeter@766:
kpeter@864: /// The \ref HartmannOrlinMmcDefaultTraits "traits class" of the algorithm
kpeter@766: typedef TR Traits;
kpeter@766:
kpeter@766: private:
kpeter@766:
kpeter@766: TEMPLATE_DIGRAPH_TYPEDEFS(Digraph);
kpeter@766:
kpeter@766: // Data sturcture for path data
kpeter@766: struct PathData
kpeter@766: {
kpeter@864: LargeCost dist;
kpeter@766: Arc pred;
kpeter@864: PathData(LargeCost d, Arc p = INVALID) :
kpeter@767: dist(d), pred(p) {}
kpeter@766: };
kpeter@766:
kpeter@766: typedef typename Digraph::template NodeMap<std::vector<PathData> >
kpeter@766: PathDataNodeMap;
kpeter@766:
kpeter@766: private:
kpeter@766:
kpeter@766: // The digraph the algorithm runs on
kpeter@766: const Digraph &_gr;
kpeter@864: // The cost of the arcs
kpeter@864: const CostMap &_cost;
kpeter@766:
kpeter@766: // Data for storing the strongly connected components
kpeter@766: int _comp_num;
kpeter@766: typename Digraph::template NodeMap<int> _comp;
kpeter@766: std::vector<std::vector<Node> > _comp_nodes;
kpeter@766: std::vector<Node>* _nodes;
kpeter@766: typename Digraph::template NodeMap<std::vector<Arc> > _out_arcs;
kpeter@766:
kpeter@766: // Data for the found cycles
kpeter@766: bool _curr_found, _best_found;
kpeter@864: LargeCost _curr_cost, _best_cost;
kpeter@766: int _curr_size, _best_size;
kpeter@766: Node _curr_node, _best_node;
kpeter@766: int _curr_level, _best_level;
kpeter@766:
kpeter@766: Path *_cycle_path;
kpeter@766: bool _local_path;
kpeter@766:
kpeter@766: // Node map for storing path data
kpeter@766: PathDataNodeMap _data;
kpeter@766: // The processed nodes in the last round
kpeter@766: std::vector<Node> _process;
kpeter@766:
kpeter@766: Tolerance _tolerance;
kpeter@766:
kpeter@767: // Infinite constant
kpeter@864: const LargeCost INF;
kpeter@767:
kpeter@766: public:
kpeter@766:
kpeter@766: /// \name Named Template Parameters
kpeter@766: /// @{
kpeter@766:
kpeter@766: template <typename T>
kpeter@864: struct SetLargeCostTraits : public Traits {
kpeter@864: typedef T LargeCost;
kpeter@766: typedef lemon::Tolerance<T> Tolerance;
kpeter@766: };
kpeter@766:
kpeter@766: /// \brief \ref named-templ-param "Named parameter" for setting
kpeter@864: /// \c LargeCost type.
kpeter@766: ///
kpeter@864: /// \ref named-templ-param "Named parameter" for setting \c LargeCost
kpeter@766: /// type. It is used for internal computations in the algorithm.
kpeter@766: template <typename T>
kpeter@864: struct SetLargeCost
kpeter@864: : public HartmannOrlinMmc<GR, CM, SetLargeCostTraits<T> > {
kpeter@864: typedef HartmannOrlinMmc<GR, CM, SetLargeCostTraits<T> > Create;
kpeter@766: };
kpeter@766:
kpeter@766: template <typename T>
kpeter@766: struct SetPathTraits : public Traits {
kpeter@766: typedef T Path;
kpeter@766: };
kpeter@766:
kpeter@766: /// \brief \ref named-templ-param "Named parameter" for setting
kpeter@766: /// \c %Path type.
kpeter@766: ///
kpeter@766: /// \ref named-templ-param "Named parameter" for setting the \c %Path
kpeter@766: /// type of the found cycles.
kpeter@766: /// It must conform to the \ref lemon::concepts::Path "Path" concept
kpeter@766: /// and it must have an \c addFront() function.
kpeter@766: template <typename T>
kpeter@766: struct SetPath
kpeter@864: : public HartmannOrlinMmc<GR, CM, SetPathTraits<T> > {
kpeter@864: typedef HartmannOrlinMmc<GR, CM, SetPathTraits<T> > Create;
kpeter@766: };
kpeter@766:
kpeter@766: /// @}
kpeter@766:
kpeter@863: protected:
kpeter@863:
kpeter@864: HartmannOrlinMmc() {}
kpeter@863:
kpeter@766: public:
kpeter@766:
kpeter@766: /// \brief Constructor.
kpeter@766: ///
kpeter@766: /// The constructor of the class.
kpeter@766: ///
kpeter@766: /// \param digraph The digraph the algorithm runs on.
kpeter@864: /// \param cost The costs of the arcs.
kpeter@864: HartmannOrlinMmc( const Digraph &digraph,
kpeter@864: const CostMap &cost ) :
kpeter@864: _gr(digraph), _cost(cost), _comp(digraph), _out_arcs(digraph),
kpeter@864: _best_found(false), _best_cost(0), _best_size(1),
kpeter@767: _cycle_path(NULL), _local_path(false), _data(digraph),
kpeter@864: INF(std::numeric_limits<LargeCost>::has_infinity ?
kpeter@864: std::numeric_limits<LargeCost>::infinity() :
kpeter@864: std::numeric_limits<LargeCost>::max())
kpeter@766: {}
kpeter@766:
kpeter@766: /// Destructor.
kpeter@864: ~HartmannOrlinMmc() {
kpeter@766: if (_local_path) delete _cycle_path;
kpeter@766: }
kpeter@766:
kpeter@766: /// \brief Set the path structure for storing the found cycle.
kpeter@766: ///
kpeter@766: /// This function sets an external path structure for storing the
kpeter@766: /// found cycle.
kpeter@766: ///
kpeter@766: /// If you don't call this function before calling \ref run() or
kpeter@864: /// \ref findCycleMean(), it will allocate a local \ref Path "path"
kpeter@766: /// structure. The destuctor deallocates this automatically
kpeter@766: /// allocated object, of course.
kpeter@766: ///
kpeter@766: /// \note The algorithm calls only the \ref lemon::Path::addFront()
kpeter@766: /// "addFront()" function of the given path structure.
kpeter@766: ///
kpeter@766: /// \return <tt>(*this)</tt>
kpeter@864: HartmannOrlinMmc& cycle(Path &path) {
kpeter@766: if (_local_path) {
kpeter@766: delete _cycle_path;
kpeter@766: _local_path = false;
kpeter@766: }
kpeter@766: _cycle_path = &path;
kpeter@766: return *this;
kpeter@766: }
kpeter@766:
kpeter@769: /// \brief Set the tolerance used by the algorithm.
kpeter@769: ///
kpeter@769: /// This function sets the tolerance object used by the algorithm.
kpeter@769: ///
kpeter@769: /// \return <tt>(*this)</tt>
kpeter@864: HartmannOrlinMmc& tolerance(const Tolerance& tolerance) {
kpeter@769: _tolerance = tolerance;
kpeter@769: return *this;
kpeter@769: }
kpeter@769:
kpeter@769: /// \brief Return a const reference to the tolerance.
kpeter@769: ///
kpeter@769: /// This function returns a const reference to the tolerance object
kpeter@769: /// used by the algorithm.
kpeter@769: const Tolerance& tolerance() const {
kpeter@769: return _tolerance;
kpeter@769: }
kpeter@769:
kpeter@766: /// \name Execution control
kpeter@766: /// The simplest way to execute the algorithm is to call the \ref run()
kpeter@766: /// function.\n
kpeter@864: /// If you only need the minimum mean cost, you may call
kpeter@864: /// \ref findCycleMean().
kpeter@766:
kpeter@766: /// @{
kpeter@766:
kpeter@766: /// \brief Run the algorithm.
kpeter@766: ///
kpeter@766: /// This function runs the algorithm.
kpeter@766: /// It can be called more than once (e.g. if the underlying digraph
kpeter@864: /// and/or the arc costs have been modified).
kpeter@766: ///
kpeter@766: /// \return \c true if a directed cycle exists in the digraph.
kpeter@766: ///
kpeter@766: /// \note <tt>mmc.run()</tt> is just a shortcut of the following code.
kpeter@766: /// \code
kpeter@864: /// return mmc.findCycleMean() && mmc.findCycle();
kpeter@766: /// \endcode
kpeter@766: bool run() {
kpeter@864: return findCycleMean() && findCycle();
kpeter@766: }
kpeter@766:
kpeter@766: /// \brief Find the minimum cycle mean.
kpeter@766: ///
kpeter@864: /// This function finds the minimum mean cost of the directed
kpeter@766: /// cycles in the digraph.
kpeter@766: ///
kpeter@766: /// \return \c true if a directed cycle exists in the digraph.
kpeter@864: bool findCycleMean() {
kpeter@766: // Initialization and find strongly connected components
kpeter@766: init();
kpeter@766: findComponents();
alpar@877:
kpeter@766: // Find the minimum cycle mean in the components
kpeter@766: for (int comp = 0; comp < _comp_num; ++comp) {
kpeter@766: if (!initComponent(comp)) continue;
kpeter@766: processRounds();
alpar@877:
kpeter@766: // Update the best cycle (global minimum mean cycle)
alpar@877: if ( _curr_found && (!_best_found ||
kpeter@864: _curr_cost * _best_size < _best_cost * _curr_size) ) {
kpeter@766: _best_found = true;
kpeter@864: _best_cost = _curr_cost;
kpeter@766: _best_size = _curr_size;
kpeter@766: _best_node = _curr_node;
kpeter@766: _best_level = _curr_level;
kpeter@766: }
kpeter@766: }
kpeter@766: return _best_found;
kpeter@766: }
kpeter@766:
kpeter@766: /// \brief Find a minimum mean directed cycle.
kpeter@766: ///
kpeter@864: /// This function finds a directed cycle of minimum mean cost
kpeter@864: /// in the digraph using the data computed by findCycleMean().
kpeter@766: ///
kpeter@766: /// \return \c true if a directed cycle exists in the digraph.
kpeter@766: ///
kpeter@864: /// \pre \ref findCycleMean() must be called before using this function.
kpeter@766: bool findCycle() {
kpeter@766: if (!_best_found) return false;
kpeter@766: IntNodeMap reached(_gr, -1);
kpeter@766: int r = _best_level + 1;
kpeter@766: Node u = _best_node;
kpeter@766: while (reached[u] < 0) {
kpeter@766: reached[u] = --r;
kpeter@766: u = _gr.source(_data[u][r].pred);
kpeter@766: }
kpeter@766: r = reached[u];
kpeter@766: Arc e = _data[u][r].pred;
kpeter@766: _cycle_path->addFront(e);
kpeter@864: _best_cost = _cost[e];
kpeter@766: _best_size = 1;
kpeter@766: Node v;
kpeter@766: while ((v = _gr.source(e)) != u) {
kpeter@766: e = _data[v][--r].pred;
kpeter@766: _cycle_path->addFront(e);
kpeter@864: _best_cost += _cost[e];
kpeter@766: ++_best_size;
kpeter@766: }
kpeter@766: return true;
kpeter@766: }
kpeter@766:
kpeter@766: /// @}
kpeter@766:
kpeter@766: /// \name Query Functions
kpeter@766: /// The results of the algorithm can be obtained using these
kpeter@766: /// functions.\n
kpeter@766: /// The algorithm should be executed before using them.
kpeter@766:
kpeter@766: /// @{
kpeter@766:
kpeter@864: /// \brief Return the total cost of the found cycle.
kpeter@766: ///
kpeter@864: /// This function returns the total cost of the found cycle.
kpeter@766: ///
kpeter@864: /// \pre \ref run() or \ref findCycleMean() must be called before
kpeter@766: /// using this function.
kpeter@864: Cost cycleCost() const {
kpeter@864: return static_cast<Cost>(_best_cost);
kpeter@766: }
kpeter@766:
kpeter@766: /// \brief Return the number of arcs on the found cycle.
kpeter@766: ///
kpeter@766: /// This function returns the number of arcs on the found cycle.
kpeter@766: ///
kpeter@864: /// \pre \ref run() or \ref findCycleMean() must be called before
kpeter@766: /// using this function.
kpeter@864: int cycleSize() const {
kpeter@766: return _best_size;
kpeter@766: }
kpeter@766:
kpeter@864: /// \brief Return the mean cost of the found cycle.
kpeter@766: ///
kpeter@864: /// This function returns the mean cost of the found cycle.
kpeter@766: ///
kpeter@766: /// \note <tt>alg.cycleMean()</tt> is just a shortcut of the
kpeter@766: /// following code.
kpeter@766: /// \code
kpeter@864: /// return static_cast<double>(alg.cycleCost()) / alg.cycleSize();
kpeter@766: /// \endcode
kpeter@766: ///
kpeter@864: /// \pre \ref run() or \ref findCycleMean() must be called before
kpeter@766: /// using this function.
kpeter@766: double cycleMean() const {
kpeter@864: return static_cast<double>(_best_cost) / _best_size;
kpeter@766: }
kpeter@766:
kpeter@766: /// \brief Return the found cycle.
kpeter@766: ///
kpeter@766: /// This function returns a const reference to the path structure
kpeter@766: /// storing the found cycle.
kpeter@766: ///
kpeter@766: /// \pre \ref run() or \ref findCycle() must be called before using
kpeter@766: /// this function.
kpeter@766: const Path& cycle() const {
kpeter@766: return *_cycle_path;
kpeter@766: }
kpeter@766:
kpeter@766: ///@}
kpeter@766:
kpeter@766: private:
kpeter@766:
kpeter@766: // Initialization
kpeter@766: void init() {
kpeter@766: if (!_cycle_path) {
kpeter@766: _local_path = true;
kpeter@766: _cycle_path = new Path;
kpeter@766: }
kpeter@766: _cycle_path->clear();
kpeter@766: _best_found = false;
kpeter@864: _best_cost = 0;
kpeter@766: _best_size = 1;
kpeter@766: _cycle_path->clear();
kpeter@766: for (NodeIt u(_gr); u != INVALID; ++u)
kpeter@766: _data[u].clear();
kpeter@766: }
kpeter@766:
kpeter@766: // Find strongly connected components and initialize _comp_nodes
kpeter@766: // and _out_arcs
kpeter@766: void findComponents() {
kpeter@766: _comp_num = stronglyConnectedComponents(_gr, _comp);
kpeter@766: _comp_nodes.resize(_comp_num);
kpeter@766: if (_comp_num == 1) {
kpeter@766: _comp_nodes[0].clear();
kpeter@766: for (NodeIt n(_gr); n != INVALID; ++n) {
kpeter@766: _comp_nodes[0].push_back(n);
kpeter@766: _out_arcs[n].clear();
kpeter@766: for (OutArcIt a(_gr, n); a != INVALID; ++a) {
kpeter@766: _out_arcs[n].push_back(a);
kpeter@766: }
kpeter@766: }
kpeter@766: } else {
kpeter@766: for (int i = 0; i < _comp_num; ++i)
kpeter@766: _comp_nodes[i].clear();
kpeter@766: for (NodeIt n(_gr); n != INVALID; ++n) {
kpeter@766: int k = _comp[n];
kpeter@766: _comp_nodes[k].push_back(n);
kpeter@766: _out_arcs[n].clear();
kpeter@766: for (OutArcIt a(_gr, n); a != INVALID; ++a) {
kpeter@766: if (_comp[_gr.target(a)] == k) _out_arcs[n].push_back(a);
kpeter@766: }
kpeter@766: }
kpeter@766: }
kpeter@766: }
kpeter@766:
kpeter@766: // Initialize path data for the current component
kpeter@766: bool initComponent(int comp) {
kpeter@766: _nodes = &(_comp_nodes[comp]);
kpeter@766: int n = _nodes->size();
kpeter@766: if (n < 1 || (n == 1 && _out_arcs[(*_nodes)[0]].size() == 0)) {
kpeter@766: return false;
alpar@877: }
kpeter@766: for (int i = 0; i < n; ++i) {
kpeter@767: _data[(*_nodes)[i]].resize(n + 1, PathData(INF));
kpeter@766: }
kpeter@766: return true;
kpeter@766: }
kpeter@766:
kpeter@766: // Process all rounds of computing path data for the current component.
kpeter@864: // _data[v][k] is the cost of a shortest directed walk from the root
kpeter@766: // node to node v containing exactly k arcs.
kpeter@766: void processRounds() {
kpeter@766: Node start = (*_nodes)[0];
kpeter@767: _data[start][0] = PathData(0);
kpeter@766: _process.clear();
kpeter@766: _process.push_back(start);
kpeter@766:
kpeter@766: int k, n = _nodes->size();
kpeter@766: int next_check = 4;
kpeter@766: bool terminate = false;
kpeter@766: for (k = 1; k <= n && int(_process.size()) < n && !terminate; ++k) {
kpeter@766: processNextBuildRound(k);
kpeter@766: if (k == next_check || k == n) {
kpeter@766: terminate = checkTermination(k);
kpeter@766: next_check = next_check * 3 / 2;
kpeter@766: }
kpeter@766: }
kpeter@766: for ( ; k <= n && !terminate; ++k) {
kpeter@766: processNextFullRound(k);
kpeter@766: if (k == next_check || k == n) {
kpeter@766: terminate = checkTermination(k);
kpeter@766: next_check = next_check * 3 / 2;
kpeter@766: }
kpeter@766: }
kpeter@766: }
kpeter@766:
kpeter@766: // Process one round and rebuild _process
kpeter@766: void processNextBuildRound(int k) {
kpeter@766: std::vector<Node> next;
kpeter@766: Node u, v;
kpeter@766: Arc e;
kpeter@864: LargeCost d;
kpeter@766: for (int i = 0; i < int(_process.size()); ++i) {
kpeter@766: u = _process[i];
kpeter@766: for (int j = 0; j < int(_out_arcs[u].size()); ++j) {
kpeter@766: e = _out_arcs[u][j];
kpeter@766: v = _gr.target(e);
kpeter@864: d = _data[u][k-1].dist + _cost[e];
kpeter@767: if (_tolerance.less(d, _data[v][k].dist)) {
kpeter@767: if (_data[v][k].dist == INF) next.push_back(v);
kpeter@767: _data[v][k] = PathData(d, e);
kpeter@766: }
kpeter@766: }
kpeter@766: }
kpeter@766: _process.swap(next);
kpeter@766: }
kpeter@766:
kpeter@766: // Process one round using _nodes instead of _process
kpeter@766: void processNextFullRound(int k) {
kpeter@766: Node u, v;
kpeter@766: Arc e;
kpeter@864: LargeCost d;
kpeter@766: for (int i = 0; i < int(_nodes->size()); ++i) {
kpeter@766: u = (*_nodes)[i];
kpeter@766: for (int j = 0; j < int(_out_arcs[u].size()); ++j) {
kpeter@766: e = _out_arcs[u][j];
kpeter@766: v = _gr.target(e);
kpeter@864: d = _data[u][k-1].dist + _cost[e];
kpeter@767: if (_tolerance.less(d, _data[v][k].dist)) {
kpeter@767: _data[v][k] = PathData(d, e);
kpeter@766: }
kpeter@766: }
kpeter@766: }
kpeter@766: }
alpar@877:
kpeter@766: // Check early termination
kpeter@766: bool checkTermination(int k) {
kpeter@766: typedef std::pair<int, int> Pair;
kpeter@766: typename GR::template NodeMap<Pair> level(_gr, Pair(-1, 0));
kpeter@864: typename GR::template NodeMap<LargeCost> pi(_gr);
kpeter@766: int n = _nodes->size();
kpeter@864: LargeCost cost;
kpeter@766: int size;
kpeter@766: Node u;
alpar@877:
kpeter@766: // Search for cycles that are already found
kpeter@766: _curr_found = false;
kpeter@766: for (int i = 0; i < n; ++i) {
kpeter@766: u = (*_nodes)[i];
kpeter@767: if (_data[u][k].dist == INF) continue;
kpeter@766: for (int j = k; j >= 0; --j) {
kpeter@766: if (level[u].first == i && level[u].second > 0) {
kpeter@766: // A cycle is found
kpeter@864: cost = _data[u][level[u].second].dist - _data[u][j].dist;
kpeter@766: size = level[u].second - j;
kpeter@864: if (!_curr_found || cost * _curr_size < _curr_cost * size) {
kpeter@864: _curr_cost = cost;
kpeter@766: _curr_size = size;
kpeter@766: _curr_node = u;
kpeter@766: _curr_level = level[u].second;
kpeter@766: _curr_found = true;
kpeter@766: }
kpeter@766: }
kpeter@766: level[u] = Pair(i, j);
deba@795: if (j != 0) {
alpar@877: u = _gr.source(_data[u][j].pred);
alpar@877: }
kpeter@766: }
kpeter@766: }
kpeter@766:
kpeter@766: // If at least one cycle is found, check the optimality condition
kpeter@864: LargeCost d;
kpeter@766: if (_curr_found && k < n) {
kpeter@766: // Find node potentials
kpeter@766: for (int i = 0; i < n; ++i) {
kpeter@766: u = (*_nodes)[i];
kpeter@767: pi[u] = INF;
kpeter@766: for (int j = 0; j <= k; ++j) {
kpeter@767: if (_data[u][j].dist < INF) {
kpeter@864: d = _data[u][j].dist * _curr_size - j * _curr_cost;
kpeter@767: if (_tolerance.less(d, pi[u])) pi[u] = d;
kpeter@766: }
kpeter@766: }
kpeter@766: }
kpeter@766:
kpeter@766: // Check the optimality condition for all arcs
kpeter@766: bool done = true;
kpeter@766: for (ArcIt a(_gr); a != INVALID; ++a) {
kpeter@864: if (_tolerance.less(_cost[a] * _curr_size - _curr_cost,
kpeter@766: pi[_gr.target(a)] - pi[_gr.source(a)]) ) {
kpeter@766: done = false;
kpeter@766: break;
kpeter@766: }
kpeter@766: }
kpeter@766: return done;
kpeter@766: }
kpeter@766: return (k == n);
kpeter@766: }
kpeter@766:
kpeter@864: }; //class HartmannOrlinMmc
kpeter@766:
kpeter@766: ///@}
kpeter@766:
kpeter@766: } //namespace lemon
kpeter@766:
kpeter@864: #endif //LEMON_HARTMANN_ORLIN_MMC_H