lemon/preflow.h
author deba
Tue, 25 Mar 2008 16:28:06 +0000
changeset 2598 71f4bd3a9ae8
parent 2527 10f3b3286e63
child 2618 6aa6fcaeaea5
permissions -rw-r--r--
Minor bug fix
     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_PREFLOW_H
    20 #define LEMON_PREFLOW_H
    21 
    22 #include <lemon/error.h>
    23 #include <lemon/bits/invalid.h>
    24 #include <lemon/tolerance.h>
    25 #include <lemon/maps.h>
    26 #include <lemon/graph_utils.h>
    27 #include <lemon/elevator.h>
    28 
    29 /// \file
    30 /// \ingroup max_flow
    31 /// \brief Implementation of the preflow algorithm.
    32 
    33 namespace lemon { 
    34   
    35   /// \brief Default traits class of Preflow class.
    36   ///
    37   /// Default traits class of Preflow class.
    38   /// \param _Graph Graph type.
    39   /// \param _CapacityMap Type of capacity map.
    40   template <typename _Graph, typename _CapacityMap>
    41   struct PreflowDefaultTraits {
    42 
    43     /// \brief The graph type the algorithm runs on. 
    44     typedef _Graph Graph;
    45 
    46     /// \brief The type of the map that stores the edge capacities.
    47     ///
    48     /// The type of the map that stores the edge capacities.
    49     /// It must meet the \ref concepts::ReadMap "ReadMap" concept.
    50     typedef _CapacityMap CapacityMap;
    51 
    52     /// \brief The type of the length of the edges.
    53     typedef typename CapacityMap::Value Value;
    54 
    55     /// \brief The map type that stores the flow values.
    56     ///
    57     /// The map type that stores the flow values. 
    58     /// It must meet the \ref concepts::ReadWriteMap "ReadWriteMap" concept.
    59     typedef typename Graph::template EdgeMap<Value> FlowMap;
    60 
    61     /// \brief Instantiates a FlowMap.
    62     ///
    63     /// This function instantiates a \ref FlowMap. 
    64     /// \param graph The graph, to which we would like to define the flow map.
    65     static FlowMap* createFlowMap(const Graph& graph) {
    66       return new FlowMap(graph);
    67     }
    68 
    69     /// \brief The eleavator type used by Preflow algorithm.
    70     /// 
    71     /// The elevator type used by Preflow algorithm.
    72     ///
    73     /// \sa Elevator
    74     /// \sa LinkedElevator
    75     typedef LinkedElevator<Graph, typename Graph::Node> Elevator;
    76     
    77     /// \brief Instantiates an Elevator.
    78     ///
    79     /// This function instantiates a \ref Elevator. 
    80     /// \param graph The graph, to which we would like to define the elevator.
    81     /// \param max_level The maximum level of the elevator.
    82     static Elevator* createElevator(const Graph& graph, int max_level) {
    83       return new Elevator(graph, max_level);
    84     }
    85 
    86     /// \brief The tolerance used by the algorithm
    87     ///
    88     /// The tolerance used by the algorithm to handle inexact computation.
    89     typedef Tolerance<Value> Tolerance;
    90 
    91   };
    92   
    93 
    94   /// \ingroup max_flow
    95   ///
    96   /// \brief %Preflow algorithms class.
    97   ///
    98   /// This class provides an implementation of the Goldberg's \e
    99   /// preflow \e algorithm producing a flow of maximum value in a
   100   /// directed graph. The preflow algorithms are the fastest known max
   101   /// flow algorithms. The current implementation use a mixture of the
   102   /// \e "highest label" and the \e "bound decrease" heuristics.
   103   /// The worst case time complexity of the algorithm is \f$O(n^2\sqrt{e})\f$.
   104   ///
   105   /// The algorithm consists from two phases. After the first phase
   106   /// the maximal flow value and the minimum cut can be obtained. The
   107   /// second phase constructs the feasible maximum flow on each edge.
   108   ///
   109   /// \param _Graph The directed graph type the algorithm runs on.
   110   /// \param _CapacityMap The flow map type.
   111   /// \param _Traits Traits class to set various data types used by
   112   /// the algorithm.  The default traits class is \ref
   113   /// PreflowDefaultTraits.  See \ref PreflowDefaultTraits for the
   114   /// documentation of a %Preflow traits class. 
   115   ///
   116   ///\author Jacint Szabo and Balazs Dezso
   117 #ifdef DOXYGEN
   118   template <typename _Graph, typename _CapacityMap, typename _Traits>
   119 #else
   120   template <typename _Graph, 
   121 	    typename _CapacityMap = typename _Graph::template EdgeMap<int>,
   122 	    typename _Traits = PreflowDefaultTraits<_Graph, _CapacityMap> >
   123 #endif
   124   class Preflow {
   125   public:
   126     
   127     typedef _Traits Traits;
   128     typedef typename Traits::Graph Graph;
   129     typedef typename Traits::CapacityMap CapacityMap;
   130     typedef typename Traits::Value Value; 
   131 
   132     typedef typename Traits::FlowMap FlowMap;
   133     typedef typename Traits::Elevator Elevator;
   134     typedef typename Traits::Tolerance Tolerance;
   135 
   136     /// \brief \ref Exception for uninitialized parameters.
   137     ///
   138     /// This error represents problems in the initialization
   139     /// of the parameters of the algorithms.
   140     class UninitializedParameter : public lemon::UninitializedParameter {
   141     public:
   142       virtual const char* what() const throw() {
   143 	return "lemon::Preflow::UninitializedParameter";
   144       }
   145     };
   146 
   147   private:
   148 
   149     GRAPH_TYPEDEFS(typename Graph);
   150 
   151     const Graph& _graph;
   152     const CapacityMap* _capacity;
   153 
   154     int _node_num;
   155 
   156     Node _source, _target;
   157 
   158     FlowMap* _flow;
   159     bool _local_flow;
   160 
   161     Elevator* _level;
   162     bool _local_level;
   163 
   164     typedef typename Graph::template NodeMap<Value> ExcessMap;
   165     ExcessMap* _excess;
   166 
   167     Tolerance _tolerance;
   168 
   169     bool _phase;
   170 
   171 
   172     void createStructures() {
   173       _node_num = countNodes(_graph);
   174 
   175       if (!_flow) {
   176 	_flow = Traits::createFlowMap(_graph);
   177 	_local_flow = true;
   178       }
   179       if (!_level) {
   180 	_level = Traits::createElevator(_graph, _node_num);
   181 	_local_level = true;
   182       }
   183       if (!_excess) {
   184 	_excess = new ExcessMap(_graph);
   185       }
   186     }
   187 
   188     void destroyStructures() {
   189       if (_local_flow) {
   190 	delete _flow;
   191       }
   192       if (_local_level) {
   193 	delete _level;
   194       }
   195       if (_excess) {
   196 	delete _excess;
   197       }
   198     }
   199 
   200   public:
   201 
   202     typedef Preflow Create;
   203 
   204     ///\name Named template parameters
   205 
   206     ///@{
   207 
   208     template <typename _FlowMap>
   209     struct DefFlowMapTraits : public Traits {
   210       typedef _FlowMap FlowMap;
   211       static FlowMap *createFlowMap(const Graph&) {
   212 	throw UninitializedParameter();
   213       }
   214     };
   215 
   216     /// \brief \ref named-templ-param "Named parameter" for setting
   217     /// FlowMap type
   218     ///
   219     /// \ref named-templ-param "Named parameter" for setting FlowMap
   220     /// type
   221     template <typename _FlowMap>
   222     struct DefFlowMap 
   223       : public Preflow<Graph, CapacityMap, DefFlowMapTraits<_FlowMap> > {
   224       typedef Preflow<Graph, CapacityMap, DefFlowMapTraits<_FlowMap> > Create;
   225     };
   226 
   227     template <typename _Elevator>
   228     struct DefElevatorTraits : public Traits {
   229       typedef _Elevator Elevator;
   230       static Elevator *createElevator(const Graph&, int) {
   231 	throw UninitializedParameter();
   232       }
   233     };
   234 
   235     /// \brief \ref named-templ-param "Named parameter" for setting
   236     /// Elevator type
   237     ///
   238     /// \ref named-templ-param "Named parameter" for setting Elevator
   239     /// type
   240     template <typename _Elevator>
   241     struct DefElevator 
   242       : public Preflow<Graph, CapacityMap, DefElevatorTraits<_Elevator> > {
   243       typedef Preflow<Graph, CapacityMap, DefElevatorTraits<_Elevator> > Create;
   244     };
   245 
   246     template <typename _Elevator>
   247     struct DefStandardElevatorTraits : public Traits {
   248       typedef _Elevator Elevator;
   249       static Elevator *createElevator(const Graph& graph, int max_level) {
   250 	return new Elevator(graph, max_level);
   251       }
   252     };
   253 
   254     /// \brief \ref named-templ-param "Named parameter" for setting
   255     /// Elevator type
   256     ///
   257     /// \ref named-templ-param "Named parameter" for setting Elevator
   258     /// type. The Elevator should be standard constructor interface, ie.
   259     /// the graph and the maximum level should be passed to it.
   260     template <typename _Elevator>
   261     struct DefStandardElevator 
   262       : public Preflow<Graph, CapacityMap, 
   263 		       DefStandardElevatorTraits<_Elevator> > {
   264       typedef Preflow<Graph, CapacityMap, 
   265 		      DefStandardElevatorTraits<_Elevator> > Create;
   266     };    
   267 
   268     /// @}
   269 
   270   protected:
   271     
   272     Preflow() {}
   273 
   274   public:
   275 
   276 
   277     /// \brief The constructor of the class.
   278     ///
   279     /// The constructor of the class. 
   280     /// \param graph The directed graph the algorithm runs on. 
   281     /// \param capacity The capacity of the edges. 
   282     /// \param source The source node.
   283     /// \param target The target node.
   284     Preflow(const Graph& graph, const CapacityMap& capacity, 
   285 	       Node source, Node target) 
   286       : _graph(graph), _capacity(&capacity), 
   287 	_node_num(0), _source(source), _target(target), 
   288 	_flow(0), _local_flow(false),
   289 	_level(0), _local_level(false),
   290 	_excess(0), _tolerance(), _phase() {}
   291 
   292     /// \brief Destrcutor.
   293     ///
   294     /// Destructor.
   295     ~Preflow() {
   296       destroyStructures();
   297     }
   298 
   299     /// \brief Sets the capacity map.
   300     ///
   301     /// Sets the capacity map.
   302     /// \return \c (*this)
   303     Preflow& capacityMap(const CapacityMap& map) {
   304       _capacity = &map;
   305       return *this;
   306     }
   307 
   308     /// \brief Sets the flow map.
   309     ///
   310     /// Sets the flow map.
   311     /// \return \c (*this)
   312     Preflow& flowMap(FlowMap& map) {
   313       if (_local_flow) {
   314 	delete _flow;
   315 	_local_flow = false;
   316       }
   317       _flow = &map;
   318       return *this;
   319     }
   320 
   321     /// \brief Returns the flow map.
   322     ///
   323     /// \return The flow map.
   324     const FlowMap& flowMap() {
   325       return *_flow;
   326     }
   327 
   328     /// \brief Sets the elevator.
   329     ///
   330     /// Sets the elevator.
   331     /// \return \c (*this)
   332     Preflow& elevator(Elevator& elevator) {
   333       if (_local_level) {
   334 	delete _level;
   335 	_local_level = false;
   336       }
   337       _level = &elevator;
   338       return *this;
   339     }
   340 
   341     /// \brief Returns the elevator.
   342     ///
   343     /// \return The elevator.
   344     const Elevator& elevator() {
   345       return *_level;
   346     }
   347 
   348     /// \brief Sets the source node.
   349     ///
   350     /// Sets the source node.
   351     /// \return \c (*this)
   352     Preflow& source(const Node& node) {
   353       _source = node;
   354       return *this;
   355     }
   356 
   357     /// \brief Sets the target node.
   358     ///
   359     /// Sets the target node.
   360     /// \return \c (*this)
   361     Preflow& target(const Node& node) {
   362       _target = node;
   363       return *this;
   364     }
   365  
   366     /// \brief Sets the tolerance used by algorithm.
   367     ///
   368     /// Sets the tolerance used by algorithm.
   369     Preflow& tolerance(const Tolerance& tolerance) const {
   370       _tolerance = tolerance;
   371       return *this;
   372     } 
   373 
   374     /// \brief Returns the tolerance used by algorithm.
   375     ///
   376     /// Returns the tolerance used by algorithm.
   377     const Tolerance& tolerance() const {
   378       return tolerance;
   379     } 
   380 
   381     /// \name Execution control The simplest way to execute the
   382     /// algorithm is to use one of the member functions called \c
   383     /// run().  
   384     /// \n
   385     /// If you need more control on initial solution or
   386     /// execution then you have to call one \ref init() function and then
   387     /// the startFirstPhase() and if you need the startSecondPhase().  
   388     
   389     ///@{
   390 
   391     /// \brief Initializes the internal data structures.
   392     ///
   393     /// Initializes the internal data structures.
   394     ///
   395     void init() {
   396       createStructures();
   397 
   398       _phase = true;
   399       for (NodeIt n(_graph); n != INVALID; ++n) {
   400 	_excess->set(n, 0);
   401       }
   402 
   403       for (EdgeIt e(_graph); e != INVALID; ++e) {
   404 	_flow->set(e, 0);
   405       }
   406 
   407       typename Graph::template NodeMap<bool> reached(_graph, false);
   408 
   409       _level->initStart();
   410       _level->initAddItem(_target);
   411 
   412       std::vector<Node> queue;
   413       reached.set(_source, true);
   414 
   415       queue.push_back(_target);
   416       reached.set(_target, true);
   417       while (!queue.empty()) {
   418 	_level->initNewLevel();
   419 	std::vector<Node> nqueue;
   420 	for (int i = 0; i < int(queue.size()); ++i) {
   421 	  Node n = queue[i];
   422 	  for (InEdgeIt e(_graph, n); e != INVALID; ++e) {
   423 	    Node u = _graph.source(e);
   424 	    if (!reached[u] && _tolerance.positive((*_capacity)[e])) {
   425 	      reached.set(u, true);
   426 	      _level->initAddItem(u);
   427 	      nqueue.push_back(u);
   428 	    }
   429 	  }
   430 	}
   431 	queue.swap(nqueue);
   432       }
   433       _level->initFinish();
   434 
   435       for (OutEdgeIt e(_graph, _source); e != INVALID; ++e) {
   436 	if (_tolerance.positive((*_capacity)[e])) {
   437 	  Node u = _graph.target(e);
   438 	  if ((*_level)[u] == _level->maxLevel()) continue;
   439 	  _flow->set(e, (*_capacity)[e]);
   440 	  _excess->set(u, (*_excess)[u] + (*_capacity)[e]);
   441 	  if (u != _target && !_level->active(u)) {
   442 	    _level->activate(u);
   443 	  }
   444 	}
   445       }
   446     }
   447 
   448     /// \brief Initializes the internal data structures.
   449     ///
   450     /// Initializes the internal data structures and sets the initial
   451     /// flow to the given \c flowMap. The \c flowMap should contain a
   452     /// flow or at least a preflow, ie. in each node excluding the
   453     /// target the incoming flow should greater or equal to the
   454     /// outgoing flow.
   455     /// \return %False when the given \c flowMap is not a preflow. 
   456     template <typename FlowMap>
   457     bool flowInit(const FlowMap& flowMap) {
   458       createStructures();
   459 
   460       for (EdgeIt e(_graph); e != INVALID; ++e) {
   461 	_flow->set(e, flowMap[e]);
   462       }
   463 
   464       for (NodeIt n(_graph); n != INVALID; ++n) {
   465 	Value excess = 0;
   466 	for (InEdgeIt e(_graph, n); e != INVALID; ++e) {
   467 	  excess += (*_flow)[e];
   468 	}
   469 	for (OutEdgeIt e(_graph, n); e != INVALID; ++e) {
   470 	  excess -= (*_flow)[e];
   471 	}
   472 	if (excess < 0 && n != _source) return false;
   473 	_excess->set(n, excess);
   474       }
   475 
   476       typename Graph::template NodeMap<bool> reached(_graph, false);
   477 
   478       _level->initStart();
   479       _level->initAddItem(_target);
   480 
   481       std::vector<Node> queue;
   482       reached.set(_source, true);
   483 
   484       queue.push_back(_target);
   485       reached.set(_target, true);
   486       while (!queue.empty()) {
   487 	_level->initNewLevel();
   488 	std::vector<Node> nqueue;
   489 	for (int i = 0; i < int(queue.size()); ++i) {
   490 	  Node n = queue[i];
   491 	  for (InEdgeIt e(_graph, n); e != INVALID; ++e) {
   492 	    Node u = _graph.source(e);
   493 	    if (!reached[u] && 
   494 		_tolerance.positive((*_capacity)[e] - (*_flow)[e])) {
   495 	      reached.set(u, true);
   496 	      _level->initAddItem(u);
   497 	      nqueue.push_back(u);
   498 	    }
   499 	  }
   500 	  for (OutEdgeIt e(_graph, n); e != INVALID; ++e) {
   501 	    Node v = _graph.target(e);
   502 	    if (!reached[v] && _tolerance.positive((*_flow)[e])) {
   503 	      reached.set(v, true);
   504 	      _level->initAddItem(v);
   505 	      nqueue.push_back(v);
   506 	    }
   507 	  }
   508 	}
   509 	queue.swap(nqueue);
   510       }
   511       _level->initFinish();
   512 
   513       for (OutEdgeIt e(_graph, _source); e != INVALID; ++e) {
   514 	Value rem = (*_capacity)[e] - (*_flow)[e]; 
   515 	if (_tolerance.positive(rem)) {
   516 	  Node u = _graph.target(e);
   517 	  if ((*_level)[u] == _level->maxLevel()) continue;
   518 	  _flow->set(e, (*_capacity)[e]);
   519 	  _excess->set(u, (*_excess)[u] + rem);
   520 	  if (u != _target && !_level->active(u)) {
   521 	    _level->activate(u);
   522 	  }
   523 	}
   524       }
   525       for (InEdgeIt e(_graph, _source); e != INVALID; ++e) {
   526 	Value rem = (*_flow)[e]; 
   527 	if (_tolerance.positive(rem)) {
   528 	  Node v = _graph.source(e);
   529 	  if ((*_level)[v] == _level->maxLevel()) continue;
   530 	  _flow->set(e, 0);
   531 	  _excess->set(v, (*_excess)[v] + rem);
   532 	  if (v != _target && !_level->active(v)) {
   533 	    _level->activate(v);
   534 	  }
   535 	}
   536       }
   537       return true;
   538     }
   539 
   540     /// \brief Starts the first phase of the preflow algorithm.
   541     ///
   542     /// The preflow algorithm consists of two phases, this method runs
   543     /// the first phase. After the first phase the maximum flow value
   544     /// and a minimum value cut can already be computed, although a
   545     /// maximum flow is not yet obtained. So after calling this method
   546     /// \ref flowValue() returns the value of a maximum flow and \ref
   547     /// minCut() returns a minimum cut.     
   548     /// \pre One of the \ref init() functions should be called. 
   549     void startFirstPhase() {
   550       _phase = true;
   551 
   552       Node n = _level->highestActive();
   553       int level = _level->highestActiveLevel();
   554       while (n != INVALID) {
   555 	int num = _node_num;
   556 
   557 	while (num > 0 && n != INVALID) {
   558 	  Value excess = (*_excess)[n];
   559 	  int new_level = _level->maxLevel();
   560 
   561 	  for (OutEdgeIt e(_graph, n); e != INVALID; ++e) {
   562 	    Value rem = (*_capacity)[e] - (*_flow)[e];
   563 	    if (!_tolerance.positive(rem)) continue;
   564 	    Node v = _graph.target(e);
   565 	    if ((*_level)[v] < level) {
   566 	      if (!_level->active(v) && v != _target) {
   567 		_level->activate(v);
   568 	      }
   569 	      if (!_tolerance.less(rem, excess)) {
   570 		_flow->set(e, (*_flow)[e] + excess);
   571 		_excess->set(v, (*_excess)[v] + excess);
   572 		excess = 0;
   573 		goto no_more_push_1;
   574 	      } else {
   575 		excess -= rem;
   576 		_excess->set(v, (*_excess)[v] + rem);
   577 		_flow->set(e, (*_capacity)[e]);
   578 	      }
   579 	    } else if (new_level > (*_level)[v]) {
   580 	      new_level = (*_level)[v];
   581 	    }
   582 	  }
   583 
   584 	  for (InEdgeIt e(_graph, n); e != INVALID; ++e) {
   585 	    Value rem = (*_flow)[e];
   586 	    if (!_tolerance.positive(rem)) continue;
   587 	    Node v = _graph.source(e);
   588 	    if ((*_level)[v] < level) {
   589 	      if (!_level->active(v) && v != _target) {
   590 		_level->activate(v);
   591 	      }
   592 	      if (!_tolerance.less(rem, excess)) {
   593 		_flow->set(e, (*_flow)[e] - excess);
   594 		_excess->set(v, (*_excess)[v] + excess);
   595 		excess = 0;
   596 		goto no_more_push_1;
   597 	      } else {
   598 		excess -= rem;
   599 		_excess->set(v, (*_excess)[v] + rem);
   600 		_flow->set(e, 0);
   601 	      }
   602 	    } else if (new_level > (*_level)[v]) {
   603 	      new_level = (*_level)[v];
   604 	    }
   605 	  }
   606 
   607 	no_more_push_1:
   608 
   609 	  _excess->set(n, excess);
   610 
   611 	  if (excess != 0) {
   612 	    if (new_level + 1 < _level->maxLevel()) {
   613 	      _level->liftHighestActive(new_level + 1);
   614 	    } else {
   615 	      _level->liftHighestActiveToTop();
   616 	    }
   617 	    if (_level->emptyLevel(level)) {
   618 	      _level->liftToTop(level);
   619 	    }
   620 	  } else {
   621 	    _level->deactivate(n);
   622 	  }
   623 	  
   624 	  n = _level->highestActive();
   625 	  level = _level->highestActiveLevel();
   626 	  --num;
   627 	}
   628 	
   629 	num = _node_num * 20;
   630 	while (num > 0 && n != INVALID) {
   631 	  Value excess = (*_excess)[n];
   632 	  int new_level = _level->maxLevel();
   633 
   634 	  for (OutEdgeIt e(_graph, n); e != INVALID; ++e) {
   635 	    Value rem = (*_capacity)[e] - (*_flow)[e];
   636 	    if (!_tolerance.positive(rem)) continue;
   637 	    Node v = _graph.target(e);
   638 	    if ((*_level)[v] < level) {
   639 	      if (!_level->active(v) && v != _target) {
   640 		_level->activate(v);
   641 	      }
   642 	      if (!_tolerance.less(rem, excess)) {
   643 		_flow->set(e, (*_flow)[e] + excess);
   644 		_excess->set(v, (*_excess)[v] + excess);
   645 		excess = 0;
   646 		goto no_more_push_2;
   647 	      } else {
   648 		excess -= rem;
   649 		_excess->set(v, (*_excess)[v] + rem);
   650 		_flow->set(e, (*_capacity)[e]);
   651 	      }
   652 	    } else if (new_level > (*_level)[v]) {
   653 	      new_level = (*_level)[v];
   654 	    }
   655 	  }
   656 
   657 	  for (InEdgeIt e(_graph, n); e != INVALID; ++e) {
   658 	    Value rem = (*_flow)[e];
   659 	    if (!_tolerance.positive(rem)) continue;
   660 	    Node v = _graph.source(e);
   661 	    if ((*_level)[v] < level) {
   662 	      if (!_level->active(v) && v != _target) {
   663 		_level->activate(v);
   664 	      }
   665 	      if (!_tolerance.less(rem, excess)) {
   666 		_flow->set(e, (*_flow)[e] - excess);
   667 		_excess->set(v, (*_excess)[v] + excess);
   668 		excess = 0;
   669 		goto no_more_push_2;
   670 	      } else {
   671 		excess -= rem;
   672 		_excess->set(v, (*_excess)[v] + rem);
   673 		_flow->set(e, 0);
   674 	      }
   675 	    } else if (new_level > (*_level)[v]) {
   676 	      new_level = (*_level)[v];
   677 	    }
   678 	  }
   679 
   680 	no_more_push_2:
   681 
   682 	  _excess->set(n, excess);
   683 
   684 	  if (excess != 0) {
   685 	    if (new_level + 1 < _level->maxLevel()) {
   686 	      _level->liftActiveOn(level, new_level + 1);
   687 	    } else {
   688 	      _level->liftActiveToTop(level);
   689 	    }
   690 	    if (_level->emptyLevel(level)) {
   691 	      _level->liftToTop(level);
   692 	    }
   693 	  } else {
   694 	    _level->deactivate(n);
   695 	  }
   696 
   697 	  while (level >= 0 && _level->activeFree(level)) {
   698 	    --level;
   699 	  }
   700 	  if (level == -1) {
   701 	    n = _level->highestActive();
   702 	    level = _level->highestActiveLevel();
   703 	  } else {
   704 	    n = _level->activeOn(level);
   705 	  }
   706 	  --num;
   707 	}
   708       }
   709     }
   710 
   711     /// \brief Starts the second phase of the preflow algorithm.
   712     ///
   713     /// The preflow algorithm consists of two phases, this method runs
   714     /// the second phase. After calling \ref init() and \ref
   715     /// startFirstPhase() and then \ref startSecondPhase(), \ref
   716     /// flowMap() return a maximum flow, \ref flowValue() returns the
   717     /// value of a maximum flow, \ref minCut() returns a minimum cut
   718     /// \pre The \ref init() and startFirstPhase() functions should be
   719     /// called before.
   720     void startSecondPhase() {
   721       _phase = false;
   722 
   723       typename Graph::template NodeMap<bool> reached(_graph);
   724       for (NodeIt n(_graph); n != INVALID; ++n) {
   725 	reached.set(n, (*_level)[n] < _level->maxLevel());
   726       }
   727 
   728       _level->initStart();
   729       _level->initAddItem(_source);
   730  
   731       std::vector<Node> queue;
   732       queue.push_back(_source);
   733       reached.set(_source, true);
   734 
   735       while (!queue.empty()) {
   736 	_level->initNewLevel();
   737 	std::vector<Node> nqueue;
   738 	for (int i = 0; i < int(queue.size()); ++i) {
   739 	  Node n = queue[i];
   740 	  for (OutEdgeIt e(_graph, n); e != INVALID; ++e) {
   741 	    Node v = _graph.target(e);
   742 	    if (!reached[v] && _tolerance.positive((*_flow)[e])) {
   743 	      reached.set(v, true);
   744 	      _level->initAddItem(v);
   745 	      nqueue.push_back(v);
   746 	    }
   747 	  }
   748 	  for (InEdgeIt e(_graph, n); e != INVALID; ++e) {
   749 	    Node u = _graph.source(e);
   750 	    if (!reached[u] && 
   751 		_tolerance.positive((*_capacity)[e] - (*_flow)[e])) {
   752 	      reached.set(u, true);
   753 	      _level->initAddItem(u);
   754 	      nqueue.push_back(u);
   755 	    }
   756 	  }
   757 	}
   758 	queue.swap(nqueue);
   759       }
   760       _level->initFinish();
   761 
   762       for (NodeIt n(_graph); n != INVALID; ++n) {
   763 	if (!reached[n]) {
   764 	  _level->markToBottom(n);
   765 	} else if ((*_excess)[n] > 0 && _target != n) {
   766 	  _level->activate(n);
   767 	}
   768       }
   769 
   770       Node n;
   771       while ((n = _level->highestActive()) != INVALID) {
   772 	Value excess = (*_excess)[n];
   773 	int level = _level->highestActiveLevel();
   774 	int new_level = _level->maxLevel();
   775 
   776 	for (OutEdgeIt e(_graph, n); e != INVALID; ++e) {
   777 	  Value rem = (*_capacity)[e] - (*_flow)[e];
   778 	  if (!_tolerance.positive(rem)) continue;
   779 	  Node v = _graph.target(e);
   780 	  if ((*_level)[v] < level) {
   781 	    if (!_level->active(v) && v != _source) {
   782 	      _level->activate(v);
   783 	    }
   784 	    if (!_tolerance.less(rem, excess)) {
   785 	      _flow->set(e, (*_flow)[e] + excess);
   786 	      _excess->set(v, (*_excess)[v] + excess);
   787 	      excess = 0;
   788 	      goto no_more_push;
   789 	    } else {
   790 	      excess -= rem;
   791 	      _excess->set(v, (*_excess)[v] + rem);
   792 	      _flow->set(e, (*_capacity)[e]);
   793 	    }
   794 	  } else if (new_level > (*_level)[v]) {
   795 	    new_level = (*_level)[v];
   796 	  }
   797 	}
   798 
   799 	for (InEdgeIt e(_graph, n); e != INVALID; ++e) {
   800 	  Value rem = (*_flow)[e];
   801 	  if (!_tolerance.positive(rem)) continue;
   802 	  Node v = _graph.source(e);
   803 	  if ((*_level)[v] < level) {
   804 	    if (!_level->active(v) && v != _source) {
   805 	      _level->activate(v);
   806 	    }
   807 	    if (!_tolerance.less(rem, excess)) {
   808 	      _flow->set(e, (*_flow)[e] - excess);
   809 	      _excess->set(v, (*_excess)[v] + excess);
   810 	      excess = 0;
   811 	      goto no_more_push;
   812 	    } else {
   813 	      excess -= rem;
   814 	      _excess->set(v, (*_excess)[v] + rem);
   815 	      _flow->set(e, 0);
   816 	    }
   817 	  } else if (new_level > (*_level)[v]) {
   818 	    new_level = (*_level)[v];
   819 	  }
   820 	}
   821 
   822       no_more_push:
   823 
   824 	_excess->set(n, excess);
   825       
   826 	if (excess != 0) {
   827 	  if (new_level + 1 < _level->maxLevel()) {
   828 	    _level->liftHighestActive(new_level + 1);
   829 	  } else {
   830 	    // Calculation error 
   831 	    _level->liftHighestActiveToTop();
   832 	  }
   833 	  if (_level->emptyLevel(level)) {
   834 	    // Calculation error 
   835 	    _level->liftToTop(level);
   836 	  }
   837 	} else {
   838 	  _level->deactivate(n);
   839 	}
   840 
   841       }
   842     }
   843 
   844     /// \brief Runs the preflow algorithm.  
   845     ///
   846     /// Runs the preflow algorithm.
   847     /// \note pf.run() is just a shortcut of the following code.
   848     /// \code
   849     ///   pf.init();
   850     ///   pf.startFirstPhase();
   851     ///   pf.startSecondPhase();
   852     /// \endcode
   853     void run() {
   854       init();
   855       startFirstPhase();
   856       startSecondPhase();
   857     }
   858 
   859     /// \brief Runs the preflow algorithm to compute the minimum cut.  
   860     ///
   861     /// Runs the preflow algorithm to compute the minimum cut.
   862     /// \note pf.runMinCut() is just a shortcut of the following code.
   863     /// \code
   864     ///   pf.init();
   865     ///   pf.startFirstPhase();
   866     /// \endcode
   867     void runMinCut() {
   868       init();
   869       startFirstPhase();
   870     }
   871 
   872     /// @}
   873 
   874     /// \name Query Functions
   875     /// The result of the %Preflow algorithm can be obtained using these
   876     /// functions.\n
   877     /// Before the use of these functions,
   878     /// either run() or start() must be called.
   879     
   880     ///@{
   881 
   882     /// \brief Returns the value of the maximum flow.
   883     ///
   884     /// Returns the value of the maximum flow by returning the excess
   885     /// of the target node \c t. This value equals to the value of
   886     /// the maximum flow already after the first phase.
   887     Value flowValue() const {
   888       return (*_excess)[_target];
   889     }
   890 
   891     /// \brief Returns true when the node is on the source side of minimum cut.
   892     ///
   893     /// Returns true when the node is on the source side of minimum
   894     /// cut. This method can be called both after running \ref
   895     /// startFirstPhase() and \ref startSecondPhase().
   896     bool minCut(const Node& node) const {
   897       return ((*_level)[node] == _level->maxLevel()) == _phase;
   898     }
   899  
   900     /// \brief Returns a minimum value cut.
   901     ///
   902     /// Sets the \c cutMap to the characteristic vector of a minimum value
   903     /// cut. This method can be called both after running \ref
   904     /// startFirstPhase() and \ref startSecondPhase(). The result after second
   905     /// phase could be changed slightly if inexact computation is used.
   906     /// \pre The \c cutMap should be a bool-valued node-map.
   907     template <typename CutMap>
   908     void minCutMap(CutMap& cutMap) const {
   909       for (NodeIt n(_graph); n != INVALID; ++n) {
   910 	cutMap.set(n, minCut(n));
   911       }
   912     }
   913 
   914     /// \brief Returns the flow on the edge.
   915     ///
   916     /// Sets the \c flowMap to the flow on the edges. This method can
   917     /// be called after the second phase of algorithm.
   918     Value flow(const Edge& edge) const {
   919       return (*_flow)[edge];
   920     }
   921     
   922     /// @}    
   923   };
   924 }
   925 
   926 #endif