lemon/min_mean_cycle.h
author Peter Kovacs <kpeter@inf.elte.hu>
Thu, 06 Aug 2009 20:12:43 +0200
changeset 760 83ce7ce39f21
parent 759 d66ff32624e2
child 761 5795860737f5
permissions -rw-r--r--
Rework and fix the implementation of MinMeanCycle (#179)

- Fix the handling of the cycle means.
- Many implementation improvements:
- More efficient data storage for the strongly connected
components.
- Better handling of BFS queues.
- Merge consecutive BFS searches (perform two BFS searches
instead of three).

This version is about two times faster on average and an order of
magnitude faster if there are a lot of strongly connected components.
     1 /* -*- C++ -*-
     2  *
     3  * This file is a part of LEMON, a generic C++ optimization library
     4  *
     5  * Copyright (C) 2003-2008
     6  * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
     7  * (Egervary Research Group on Combinatorial Optimization, EGRES).
     8  *
     9  * Permission to use, modify and distribute this software is granted
    10  * provided that this copyright notice appears in all copies. For
    11  * precise terms see the accompanying LICENSE file.
    12  *
    13  * This software is provided "AS IS" with no warranty of any kind,
    14  * express or implied, and with no claim as to its suitability for any
    15  * purpose.
    16  *
    17  */
    18 
    19 #ifndef LEMON_MIN_MEAN_CYCLE_H
    20 #define LEMON_MIN_MEAN_CYCLE_H
    21 
    22 /// \ingroup shortest_path
    23 ///
    24 /// \file
    25 /// \brief Howard's algorithm for finding a minimum mean cycle.
    26 
    27 #include <vector>
    28 #include <lemon/core.h>
    29 #include <lemon/path.h>
    30 #include <lemon/tolerance.h>
    31 #include <lemon/connectivity.h>
    32 
    33 namespace lemon {
    34 
    35   /// \addtogroup shortest_path
    36   /// @{
    37 
    38   /// \brief Implementation of Howard's algorithm for finding a minimum
    39   /// mean cycle.
    40   ///
    41   /// \ref MinMeanCycle implements Howard's algorithm for finding a
    42   /// directed cycle of minimum mean length (cost) in a digraph.
    43   ///
    44   /// \tparam GR The type of the digraph the algorithm runs on.
    45   /// \tparam LEN The type of the length map. The default
    46   /// map type is \ref concepts::Digraph::ArcMap "GR::ArcMap<int>".
    47   ///
    48   /// \warning \c LEN::Value must be convertible to \c double.
    49 #ifdef DOXYGEN
    50   template <typename GR, typename LEN>
    51 #else
    52   template < typename GR,
    53              typename LEN = typename GR::template ArcMap<int> >
    54 #endif
    55   class MinMeanCycle
    56   {
    57   public:
    58   
    59     /// The type of the digraph the algorithm runs on
    60     typedef GR Digraph;
    61     /// The type of the length map
    62     typedef LEN LengthMap;
    63     /// The type of the arc lengths
    64     typedef typename LengthMap::Value Value;
    65     /// The type of the paths
    66     typedef lemon::Path<Digraph> Path;
    67 
    68   private:
    69 
    70     TEMPLATE_DIGRAPH_TYPEDEFS(Digraph);
    71   
    72     // The digraph the algorithm runs on
    73     const Digraph &_gr;
    74     // The length of the arcs
    75     const LengthMap &_length;
    76 
    77     // Data for the found cycles
    78     bool _curr_found, _best_found;
    79     Value _curr_length, _best_length;
    80     int _curr_size, _best_size;
    81     Node _curr_node, _best_node;
    82 
    83     Path *_cycle_path;
    84     bool _local_path;
    85 
    86     // Internal data used by the algorithm
    87     typename Digraph::template NodeMap<Arc> _policy;
    88     typename Digraph::template NodeMap<bool> _reached;
    89     typename Digraph::template NodeMap<int> _level;
    90     typename Digraph::template NodeMap<double> _dist;
    91 
    92     // Data for storing the strongly connected components
    93     int _comp_num;
    94     typename Digraph::template NodeMap<int> _comp;
    95     std::vector<std::vector<Node> > _comp_nodes;
    96     std::vector<Node>* _nodes;
    97     typename Digraph::template NodeMap<std::vector<Arc> > _in_arcs;
    98     
    99     // Queue used for BFS search
   100     std::vector<Node> _queue;
   101     int _qfront, _qback;
   102     
   103     Tolerance<double> _tol;
   104 
   105   public:
   106 
   107     /// \brief Constructor.
   108     ///
   109     /// The constructor of the class.
   110     ///
   111     /// \param digraph The digraph the algorithm runs on.
   112     /// \param length The lengths (costs) of the arcs.
   113     MinMeanCycle( const Digraph &digraph,
   114                   const LengthMap &length ) :
   115       _gr(digraph), _length(length), _cycle_path(NULL), _local_path(false),
   116       _policy(digraph), _reached(digraph), _level(digraph), _dist(digraph),
   117       _comp(digraph), _in_arcs(digraph)
   118     {}
   119 
   120     /// Destructor.
   121     ~MinMeanCycle() {
   122       if (_local_path) delete _cycle_path;
   123     }
   124 
   125     /// \brief Set the path structure for storing the found cycle.
   126     ///
   127     /// This function sets an external path structure for storing the
   128     /// found cycle.
   129     ///
   130     /// If you don't call this function before calling \ref run() or
   131     /// \ref findMinMean(), it will allocate a local \ref Path "path"
   132     /// structure. The destuctor deallocates this automatically
   133     /// allocated object, of course.
   134     ///
   135     /// \note The algorithm calls only the \ref lemon::Path::addBack()
   136     /// "addBack()" function of the given path structure.
   137     ///
   138     /// \return <tt>(*this)</tt>
   139     ///
   140     /// \sa cycle()
   141     MinMeanCycle& cyclePath(Path &path) {
   142       if (_local_path) {
   143         delete _cycle_path;
   144         _local_path = false;
   145       }
   146       _cycle_path = &path;
   147       return *this;
   148     }
   149 
   150     /// \name Execution control
   151     /// The simplest way to execute the algorithm is to call the \ref run()
   152     /// function.\n
   153     /// If you only need the minimum mean length, you may call
   154     /// \ref findMinMean().
   155 
   156     /// @{
   157 
   158     /// \brief Run the algorithm.
   159     ///
   160     /// This function runs the algorithm.
   161     /// It can be called more than once (e.g. if the underlying digraph
   162     /// and/or the arc lengths have been modified).
   163     ///
   164     /// \return \c true if a directed cycle exists in the digraph.
   165     ///
   166     /// \note <tt>mmc.run()</tt> is just a shortcut of the following code.
   167     /// \code
   168     ///   return mmc.findMinMean() && mmc.findCycle();
   169     /// \endcode
   170     bool run() {
   171       return findMinMean() && findCycle();
   172     }
   173 
   174     /// \brief Find the minimum cycle mean.
   175     ///
   176     /// This function finds the minimum mean length of the directed
   177     /// cycles in the digraph.
   178     ///
   179     /// \return \c true if a directed cycle exists in the digraph.
   180     bool findMinMean() {
   181       // Initialize and find strongly connected components
   182       init();
   183       findComponents();
   184       
   185       // Find the minimum cycle mean in the components
   186       for (int comp = 0; comp < _comp_num; ++comp) {
   187         // Find the minimum mean cycle in the current component
   188         if (!buildPolicyGraph(comp)) continue;
   189         while (true) {
   190           findPolicyCycle();
   191           if (!computeNodeDistances()) break;
   192         }
   193         // Update the best cycle (global minimum mean cycle)
   194         if ( !_best_found || (_curr_found &&
   195              _curr_length * _best_size < _best_length * _curr_size) ) {
   196           _best_found = true;
   197           _best_length = _curr_length;
   198           _best_size = _curr_size;
   199           _best_node = _curr_node;
   200         }
   201       }
   202       return _best_found;
   203     }
   204 
   205     /// \brief Find a minimum mean directed cycle.
   206     ///
   207     /// This function finds a directed cycle of minimum mean length
   208     /// in the digraph using the data computed by findMinMean().
   209     ///
   210     /// \return \c true if a directed cycle exists in the digraph.
   211     ///
   212     /// \pre \ref findMinMean() must be called before using this function.
   213     bool findCycle() {
   214       if (!_best_found) return false;
   215       _cycle_path->addBack(_policy[_best_node]);
   216       for ( Node v = _best_node;
   217             (v = _gr.target(_policy[v])) != _best_node; ) {
   218         _cycle_path->addBack(_policy[v]);
   219       }
   220       return true;
   221     }
   222 
   223     /// @}
   224 
   225     /// \name Query Functions
   226     /// The results of the algorithm can be obtained using these
   227     /// functions.\n
   228     /// The algorithm should be executed before using them.
   229 
   230     /// @{
   231 
   232     /// \brief Return the total length of the found cycle.
   233     ///
   234     /// This function returns the total length of the found cycle.
   235     ///
   236     /// \pre \ref run() or \ref findMinMean() must be called before
   237     /// using this function.
   238     Value cycleLength() const {
   239       return _best_length;
   240     }
   241 
   242     /// \brief Return the number of arcs on the found cycle.
   243     ///
   244     /// This function returns the number of arcs on the found cycle.
   245     ///
   246     /// \pre \ref run() or \ref findMinMean() must be called before
   247     /// using this function.
   248     int cycleArcNum() const {
   249       return _best_size;
   250     }
   251 
   252     /// \brief Return the mean length of the found cycle.
   253     ///
   254     /// This function returns the mean length of the found cycle.
   255     ///
   256     /// \note <tt>alg.cycleMean()</tt> is just a shortcut of the
   257     /// following code.
   258     /// \code
   259     ///   return static_cast<double>(alg.cycleLength()) / alg.cycleArcNum();
   260     /// \endcode
   261     ///
   262     /// \pre \ref run() or \ref findMinMean() must be called before
   263     /// using this function.
   264     double cycleMean() const {
   265       return static_cast<double>(_best_length) / _best_size;
   266     }
   267 
   268     /// \brief Return the found cycle.
   269     ///
   270     /// This function returns a const reference to the path structure
   271     /// storing the found cycle.
   272     ///
   273     /// \pre \ref run() or \ref findCycle() must be called before using
   274     /// this function.
   275     ///
   276     /// \sa cyclePath()
   277     const Path& cycle() const {
   278       return *_cycle_path;
   279     }
   280 
   281     ///@}
   282 
   283   private:
   284 
   285     // Initialize
   286     void init() {
   287       _tol.epsilon(1e-6);
   288       if (!_cycle_path) {
   289         _local_path = true;
   290         _cycle_path = new Path;
   291       }
   292       _queue.resize(countNodes(_gr));
   293       _best_found = false;
   294       _best_length = 0;
   295       _best_size = 1;
   296       _cycle_path->clear();
   297     }
   298     
   299     // Find strongly connected components and initialize _comp_nodes
   300     // and _in_arcs
   301     void findComponents() {
   302       _comp_num = stronglyConnectedComponents(_gr, _comp);
   303       _comp_nodes.resize(_comp_num);
   304       if (_comp_num == 1) {
   305         _comp_nodes[0].clear();
   306         for (NodeIt n(_gr); n != INVALID; ++n) {
   307           _comp_nodes[0].push_back(n);
   308           _in_arcs[n].clear();
   309           for (InArcIt a(_gr, n); a != INVALID; ++a) {
   310             _in_arcs[n].push_back(a);
   311           }
   312         }
   313       } else {
   314         for (int i = 0; i < _comp_num; ++i)
   315           _comp_nodes[i].clear();
   316         for (NodeIt n(_gr); n != INVALID; ++n) {
   317           int k = _comp[n];
   318           _comp_nodes[k].push_back(n);
   319           _in_arcs[n].clear();
   320           for (InArcIt a(_gr, n); a != INVALID; ++a) {
   321             if (_comp[_gr.source(a)] == k) _in_arcs[n].push_back(a);
   322           }
   323         }
   324       }
   325     }
   326 
   327     // Build the policy graph in the given strongly connected component
   328     // (the out-degree of every node is 1)
   329     bool buildPolicyGraph(int comp) {
   330       _nodes = &(_comp_nodes[comp]);
   331       if (_nodes->size() < 1 ||
   332           (_nodes->size() == 1 && _in_arcs[(*_nodes)[0]].size() == 0)) {
   333         return false;
   334       }
   335       for (int i = 0; i < int(_nodes->size()); ++i) {
   336         _dist[(*_nodes)[i]] = std::numeric_limits<double>::max();
   337       }
   338       Node u, v;
   339       Arc e;
   340       for (int i = 0; i < int(_nodes->size()); ++i) {
   341         v = (*_nodes)[i];
   342         for (int j = 0; j < int(_in_arcs[v].size()); ++j) {
   343           e = _in_arcs[v][j];
   344           u = _gr.source(e);
   345           if (_length[e] < _dist[u]) {
   346             _dist[u] = _length[e];
   347             _policy[u] = e;
   348           }
   349         }
   350       }
   351       return true;
   352     }
   353 
   354     // Find the minimum mean cycle in the policy graph
   355     void findPolicyCycle() {
   356       for (int i = 0; i < int(_nodes->size()); ++i) {
   357         _level[(*_nodes)[i]] = -1;
   358       }
   359       Value clength;
   360       int csize;
   361       Node u, v;
   362       _curr_found = false;
   363       for (int i = 0; i < int(_nodes->size()); ++i) {
   364         u = (*_nodes)[i];
   365         if (_level[u] >= 0) continue;
   366         for (; _level[u] < 0; u = _gr.target(_policy[u])) {
   367           _level[u] = i;
   368         }
   369         if (_level[u] == i) {
   370           // A cycle is found
   371           clength = _length[_policy[u]];
   372           csize = 1;
   373           for (v = u; (v = _gr.target(_policy[v])) != u; ) {
   374             clength += _length[_policy[v]];
   375             ++csize;
   376           }
   377           if ( !_curr_found ||
   378                (clength * _curr_size < _curr_length * csize) ) {
   379             _curr_found = true;
   380             _curr_length = clength;
   381             _curr_size = csize;
   382             _curr_node = u;
   383           }
   384         }
   385       }
   386     }
   387 
   388     // Contract the policy graph and compute node distances
   389     bool computeNodeDistances() {
   390       // Find the component of the main cycle and compute node distances
   391       // using reverse BFS
   392       for (int i = 0; i < int(_nodes->size()); ++i) {
   393         _reached[(*_nodes)[i]] = false;
   394       }
   395       double curr_mean = double(_curr_length) / _curr_size;
   396       _qfront = _qback = 0;
   397       _queue[0] = _curr_node;
   398       _reached[_curr_node] = true;
   399       _dist[_curr_node] = 0;
   400       Node u, v;
   401       Arc e;
   402       while (_qfront <= _qback) {
   403         v = _queue[_qfront++];
   404         for (int j = 0; j < int(_in_arcs[v].size()); ++j) {
   405           e = _in_arcs[v][j];
   406           u = _gr.source(e);
   407           if (_policy[u] == e && !_reached[u]) {
   408             _reached[u] = true;
   409             _dist[u] = _dist[v] + _length[e] - curr_mean;
   410             _queue[++_qback] = u;
   411           }
   412         }
   413       }
   414 
   415       // Connect all other nodes to this component and compute node
   416       // distances using reverse BFS
   417       _qfront = 0;
   418       while (_qback < int(_nodes->size())-1) {
   419         v = _queue[_qfront++];
   420         for (int j = 0; j < int(_in_arcs[v].size()); ++j) {
   421           e = _in_arcs[v][j];
   422           u = _gr.source(e);
   423           if (!_reached[u]) {
   424             _reached[u] = true;
   425             _policy[u] = e;
   426             _dist[u] = _dist[v] + _length[e] - curr_mean;
   427             _queue[++_qback] = u;
   428           }
   429         }
   430       }
   431 
   432       // Improve node distances
   433       bool improved = false;
   434       for (int i = 0; i < int(_nodes->size()); ++i) {
   435         v = (*_nodes)[i];
   436         for (int j = 0; j < int(_in_arcs[v].size()); ++j) {
   437           e = _in_arcs[v][j];
   438           u = _gr.source(e);
   439           double delta = _dist[v] + _length[e] - curr_mean;
   440           if (_tol.less(delta, _dist[u])) {
   441             _dist[u] = delta;
   442             _policy[u] = e;
   443             improved = true;
   444           }
   445         }
   446       }
   447       return improved;
   448     }
   449 
   450   }; //class MinMeanCycle
   451 
   452   ///@}
   453 
   454 } //namespace lemon
   455 
   456 #endif //LEMON_MIN_MEAN_CYCLE_H