lemon/preflow.h
author Peter Kovacs <kpeter@inf.elte.hu>
Tue, 24 Mar 2009 00:18:25 +0100
changeset 604 8c3112a66878
parent 440 88ed40ad0d4f
child 559 c5fd2d996909
child 610 dacc2cee2b4c
permissions -rw-r--r--
Use XTI implementation instead of ATI in NetworkSimplex (#234)

XTI (eXtended Threaded Index) is an imporved version of the widely
known ATI (Augmented Threaded Index) method for storing and updating
the spanning tree structure in Network Simplex algorithms.

In the ATI data structure three indices are stored for each node:
predecessor, thread and depth. In the XTI data structure depth is
replaced by the number of successors and the last successor
(according to the thread index).
     1 /* -*- mode: C++; indent-tabs-mode: nil; -*-
     2  *
     3  * This file is a part of LEMON, a generic C++ optimization library.
     4  *
     5  * Copyright (C) 2003-2009
     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/tolerance.h>
    23 #include <lemon/elevator.h>
    24 
    25 /// \file
    26 /// \ingroup max_flow
    27 /// \brief Implementation of the preflow algorithm.
    28 
    29 namespace lemon {
    30 
    31   /// \brief Default traits class of Preflow class.
    32   ///
    33   /// Default traits class of Preflow class.
    34   /// \tparam GR Digraph type.
    35   /// \tparam CM Capacity map type.
    36   template <typename GR, typename CM>
    37   struct PreflowDefaultTraits {
    38 
    39     /// \brief The type of the digraph the algorithm runs on.
    40     typedef GR Digraph;
    41 
    42     /// \brief The type of the map that stores the arc capacities.
    43     ///
    44     /// The type of the map that stores the arc capacities.
    45     /// It must meet the \ref concepts::ReadMap "ReadMap" concept.
    46     typedef CM CapacityMap;
    47 
    48     /// \brief The type of the flow values.
    49     typedef typename CapacityMap::Value Value;
    50 
    51     /// \brief The type of the map that stores the flow values.
    52     ///
    53     /// The type of the map that stores the flow values.
    54     /// It must meet the \ref concepts::ReadWriteMap "ReadWriteMap" concept.
    55     typedef typename Digraph::template ArcMap<Value> FlowMap;
    56 
    57     /// \brief Instantiates a FlowMap.
    58     ///
    59     /// This function instantiates a \ref FlowMap.
    60     /// \param digraph The digraph, to which we would like to define
    61     /// the flow map.
    62     static FlowMap* createFlowMap(const Digraph& digraph) {
    63       return new FlowMap(digraph);
    64     }
    65 
    66     /// \brief The elevator type used by Preflow algorithm.
    67     ///
    68     /// The elevator type used by Preflow algorithm.
    69     ///
    70     /// \sa Elevator
    71     /// \sa LinkedElevator
    72     typedef LinkedElevator<Digraph, typename Digraph::Node> Elevator;
    73 
    74     /// \brief Instantiates an Elevator.
    75     ///
    76     /// This function instantiates an \ref Elevator.
    77     /// \param digraph The digraph, to which we would like to define
    78     /// the elevator.
    79     /// \param max_level The maximum level of the elevator.
    80     static Elevator* createElevator(const Digraph& digraph, int max_level) {
    81       return new Elevator(digraph, max_level);
    82     }
    83 
    84     /// \brief The tolerance used by the algorithm
    85     ///
    86     /// The tolerance used by the algorithm to handle inexact computation.
    87     typedef lemon::Tolerance<Value> Tolerance;
    88 
    89   };
    90 
    91 
    92   /// \ingroup max_flow
    93   ///
    94   /// \brief %Preflow algorithm class.
    95   ///
    96   /// This class provides an implementation of Goldberg-Tarjan's \e preflow
    97   /// \e push-relabel algorithm producing a flow of maximum value in a
    98   /// digraph. The preflow algorithms are the fastest known maximum
    99   /// flow algorithms. The current implementation use a mixture of the
   100   /// \e "highest label" and the \e "bound decrease" heuristics.
   101   /// The worst case time complexity of the algorithm is \f$O(n^2\sqrt{e})\f$.
   102   ///
   103   /// The algorithm consists of two phases. After the first phase
   104   /// the maximum flow value and the minimum cut is obtained. The
   105   /// second phase constructs a feasible maximum flow on each arc.
   106   ///
   107   /// \tparam GR The type of the digraph the algorithm runs on.
   108   /// \tparam CM The type of the capacity map. The default map
   109   /// type is \ref concepts::Digraph::ArcMap "GR::ArcMap<int>".
   110 #ifdef DOXYGEN
   111   template <typename GR, typename CM, typename TR>
   112 #else
   113   template <typename GR,
   114             typename CM = typename GR::template ArcMap<int>,
   115             typename TR = PreflowDefaultTraits<GR, CM> >
   116 #endif
   117   class Preflow {
   118   public:
   119 
   120     ///The \ref PreflowDefaultTraits "traits class" of the algorithm.
   121     typedef TR Traits;
   122     ///The type of the digraph the algorithm runs on.
   123     typedef typename Traits::Digraph Digraph;
   124     ///The type of the capacity map.
   125     typedef typename Traits::CapacityMap CapacityMap;
   126     ///The type of the flow values.
   127     typedef typename Traits::Value Value;
   128 
   129     ///The type of the flow map.
   130     typedef typename Traits::FlowMap FlowMap;
   131     ///The type of the elevator.
   132     typedef typename Traits::Elevator Elevator;
   133     ///The type of the tolerance.
   134     typedef typename Traits::Tolerance Tolerance;
   135 
   136   private:
   137 
   138     TEMPLATE_DIGRAPH_TYPEDEFS(Digraph);
   139 
   140     const Digraph& _graph;
   141     const CapacityMap* _capacity;
   142 
   143     int _node_num;
   144 
   145     Node _source, _target;
   146 
   147     FlowMap* _flow;
   148     bool _local_flow;
   149 
   150     Elevator* _level;
   151     bool _local_level;
   152 
   153     typedef typename Digraph::template NodeMap<Value> ExcessMap;
   154     ExcessMap* _excess;
   155 
   156     Tolerance _tolerance;
   157 
   158     bool _phase;
   159 
   160 
   161     void createStructures() {
   162       _node_num = countNodes(_graph);
   163 
   164       if (!_flow) {
   165         _flow = Traits::createFlowMap(_graph);
   166         _local_flow = true;
   167       }
   168       if (!_level) {
   169         _level = Traits::createElevator(_graph, _node_num);
   170         _local_level = true;
   171       }
   172       if (!_excess) {
   173         _excess = new ExcessMap(_graph);
   174       }
   175     }
   176 
   177     void destroyStructures() {
   178       if (_local_flow) {
   179         delete _flow;
   180       }
   181       if (_local_level) {
   182         delete _level;
   183       }
   184       if (_excess) {
   185         delete _excess;
   186       }
   187     }
   188 
   189   public:
   190 
   191     typedef Preflow Create;
   192 
   193     ///\name Named Template Parameters
   194 
   195     ///@{
   196 
   197     template <typename _FlowMap>
   198     struct SetFlowMapTraits : public Traits {
   199       typedef _FlowMap FlowMap;
   200       static FlowMap *createFlowMap(const Digraph&) {
   201         LEMON_ASSERT(false, "FlowMap is not initialized");
   202         return 0; // ignore warnings
   203       }
   204     };
   205 
   206     /// \brief \ref named-templ-param "Named parameter" for setting
   207     /// FlowMap type
   208     ///
   209     /// \ref named-templ-param "Named parameter" for setting FlowMap
   210     /// type.
   211     template <typename _FlowMap>
   212     struct SetFlowMap
   213       : public Preflow<Digraph, CapacityMap, SetFlowMapTraits<_FlowMap> > {
   214       typedef Preflow<Digraph, CapacityMap,
   215                       SetFlowMapTraits<_FlowMap> > Create;
   216     };
   217 
   218     template <typename _Elevator>
   219     struct SetElevatorTraits : public Traits {
   220       typedef _Elevator Elevator;
   221       static Elevator *createElevator(const Digraph&, int) {
   222         LEMON_ASSERT(false, "Elevator is not initialized");
   223         return 0; // ignore warnings
   224       }
   225     };
   226 
   227     /// \brief \ref named-templ-param "Named parameter" for setting
   228     /// Elevator type
   229     ///
   230     /// \ref named-templ-param "Named parameter" for setting Elevator
   231     /// type. If this named parameter is used, then an external
   232     /// elevator object must be passed to the algorithm using the
   233     /// \ref elevator(Elevator&) "elevator()" function before calling
   234     /// \ref run() or \ref init().
   235     /// \sa SetStandardElevator
   236     template <typename _Elevator>
   237     struct SetElevator
   238       : public Preflow<Digraph, CapacityMap, SetElevatorTraits<_Elevator> > {
   239       typedef Preflow<Digraph, CapacityMap,
   240                       SetElevatorTraits<_Elevator> > Create;
   241     };
   242 
   243     template <typename _Elevator>
   244     struct SetStandardElevatorTraits : public Traits {
   245       typedef _Elevator Elevator;
   246       static Elevator *createElevator(const Digraph& digraph, int max_level) {
   247         return new Elevator(digraph, max_level);
   248       }
   249     };
   250 
   251     /// \brief \ref named-templ-param "Named parameter" for setting
   252     /// Elevator type with automatic allocation
   253     ///
   254     /// \ref named-templ-param "Named parameter" for setting Elevator
   255     /// type with automatic allocation.
   256     /// The Elevator should have standard constructor interface to be
   257     /// able to automatically created by the algorithm (i.e. the
   258     /// digraph and the maximum level should be passed to it).
   259     /// However an external elevator object could also be passed to the
   260     /// algorithm with the \ref elevator(Elevator&) "elevator()" function
   261     /// before calling \ref run() or \ref init().
   262     /// \sa SetElevator
   263     template <typename _Elevator>
   264     struct SetStandardElevator
   265       : public Preflow<Digraph, CapacityMap,
   266                        SetStandardElevatorTraits<_Elevator> > {
   267       typedef Preflow<Digraph, CapacityMap,
   268                       SetStandardElevatorTraits<_Elevator> > Create;
   269     };
   270 
   271     /// @}
   272 
   273   protected:
   274 
   275     Preflow() {}
   276 
   277   public:
   278 
   279 
   280     /// \brief The constructor of the class.
   281     ///
   282     /// The constructor of the class.
   283     /// \param digraph The digraph the algorithm runs on.
   284     /// \param capacity The capacity of the arcs.
   285     /// \param source The source node.
   286     /// \param target The target node.
   287     Preflow(const Digraph& digraph, const CapacityMap& capacity,
   288             Node source, Node target)
   289       : _graph(digraph), _capacity(&capacity),
   290         _node_num(0), _source(source), _target(target),
   291         _flow(0), _local_flow(false),
   292         _level(0), _local_level(false),
   293         _excess(0), _tolerance(), _phase() {}
   294 
   295     /// \brief Destructor.
   296     ///
   297     /// Destructor.
   298     ~Preflow() {
   299       destroyStructures();
   300     }
   301 
   302     /// \brief Sets the capacity map.
   303     ///
   304     /// Sets the capacity map.
   305     /// \return <tt>(*this)</tt>
   306     Preflow& capacityMap(const CapacityMap& map) {
   307       _capacity = &map;
   308       return *this;
   309     }
   310 
   311     /// \brief Sets the flow map.
   312     ///
   313     /// Sets the flow map.
   314     /// If you don't use this function before calling \ref run() or
   315     /// \ref init(), an instance will be allocated automatically.
   316     /// The destructor deallocates this automatically allocated map,
   317     /// of course.
   318     /// \return <tt>(*this)</tt>
   319     Preflow& flowMap(FlowMap& map) {
   320       if (_local_flow) {
   321         delete _flow;
   322         _local_flow = false;
   323       }
   324       _flow = &map;
   325       return *this;
   326     }
   327 
   328     /// \brief Sets the source node.
   329     ///
   330     /// Sets the source node.
   331     /// \return <tt>(*this)</tt>
   332     Preflow& source(const Node& node) {
   333       _source = node;
   334       return *this;
   335     }
   336 
   337     /// \brief Sets the target node.
   338     ///
   339     /// Sets the target node.
   340     /// \return <tt>(*this)</tt>
   341     Preflow& target(const Node& node) {
   342       _target = node;
   343       return *this;
   344     }
   345 
   346     /// \brief Sets the elevator used by algorithm.
   347     ///
   348     /// Sets the elevator used by algorithm.
   349     /// If you don't use this function before calling \ref run() or
   350     /// \ref init(), an instance will be allocated automatically.
   351     /// The destructor deallocates this automatically allocated elevator,
   352     /// of course.
   353     /// \return <tt>(*this)</tt>
   354     Preflow& elevator(Elevator& elevator) {
   355       if (_local_level) {
   356         delete _level;
   357         _local_level = false;
   358       }
   359       _level = &elevator;
   360       return *this;
   361     }
   362 
   363     /// \brief Returns a const reference to the elevator.
   364     ///
   365     /// Returns a const reference to the elevator.
   366     ///
   367     /// \pre Either \ref run() or \ref init() must be called before
   368     /// using this function.
   369     const Elevator& elevator() const {
   370       return *_level;
   371     }
   372 
   373     /// \brief Sets the tolerance used by algorithm.
   374     ///
   375     /// Sets the tolerance used by algorithm.
   376     Preflow& tolerance(const Tolerance& tolerance) const {
   377       _tolerance = tolerance;
   378       return *this;
   379     }
   380 
   381     /// \brief Returns a const reference to the tolerance.
   382     ///
   383     /// Returns a const reference to the tolerance.
   384     const Tolerance& tolerance() const {
   385       return tolerance;
   386     }
   387 
   388     /// \name Execution Control
   389     /// The simplest way to execute the preflow algorithm is to use
   390     /// \ref run() or \ref runMinCut().\n
   391     /// If you need more control on the initial solution or the execution,
   392     /// first you have to call one of the \ref init() functions, then
   393     /// \ref startFirstPhase() and if you need it \ref startSecondPhase().
   394 
   395     ///@{
   396 
   397     /// \brief Initializes the internal data structures.
   398     ///
   399     /// Initializes the internal data structures and sets the initial
   400     /// flow to zero on each arc.
   401     void init() {
   402       createStructures();
   403 
   404       _phase = true;
   405       for (NodeIt n(_graph); n != INVALID; ++n) {
   406         _excess->set(n, 0);
   407       }
   408 
   409       for (ArcIt e(_graph); e != INVALID; ++e) {
   410         _flow->set(e, 0);
   411       }
   412 
   413       typename Digraph::template NodeMap<bool> reached(_graph, false);
   414 
   415       _level->initStart();
   416       _level->initAddItem(_target);
   417 
   418       std::vector<Node> queue;
   419       reached.set(_source, true);
   420 
   421       queue.push_back(_target);
   422       reached.set(_target, true);
   423       while (!queue.empty()) {
   424         _level->initNewLevel();
   425         std::vector<Node> nqueue;
   426         for (int i = 0; i < int(queue.size()); ++i) {
   427           Node n = queue[i];
   428           for (InArcIt e(_graph, n); e != INVALID; ++e) {
   429             Node u = _graph.source(e);
   430             if (!reached[u] && _tolerance.positive((*_capacity)[e])) {
   431               reached.set(u, true);
   432               _level->initAddItem(u);
   433               nqueue.push_back(u);
   434             }
   435           }
   436         }
   437         queue.swap(nqueue);
   438       }
   439       _level->initFinish();
   440 
   441       for (OutArcIt e(_graph, _source); e != INVALID; ++e) {
   442         if (_tolerance.positive((*_capacity)[e])) {
   443           Node u = _graph.target(e);
   444           if ((*_level)[u] == _level->maxLevel()) continue;
   445           _flow->set(e, (*_capacity)[e]);
   446           _excess->set(u, (*_excess)[u] + (*_capacity)[e]);
   447           if (u != _target && !_level->active(u)) {
   448             _level->activate(u);
   449           }
   450         }
   451       }
   452     }
   453 
   454     /// \brief Initializes the internal data structures using the
   455     /// given flow map.
   456     ///
   457     /// Initializes the internal data structures and sets the initial
   458     /// flow to the given \c flowMap. The \c flowMap should contain a
   459     /// flow or at least a preflow, i.e. at each node excluding the
   460     /// source node the incoming flow should greater or equal to the
   461     /// outgoing flow.
   462     /// \return \c false if the given \c flowMap is not a preflow.
   463     template <typename FlowMap>
   464     bool init(const FlowMap& flowMap) {
   465       createStructures();
   466 
   467       for (ArcIt e(_graph); e != INVALID; ++e) {
   468         _flow->set(e, flowMap[e]);
   469       }
   470 
   471       for (NodeIt n(_graph); n != INVALID; ++n) {
   472         Value excess = 0;
   473         for (InArcIt e(_graph, n); e != INVALID; ++e) {
   474           excess += (*_flow)[e];
   475         }
   476         for (OutArcIt e(_graph, n); e != INVALID; ++e) {
   477           excess -= (*_flow)[e];
   478         }
   479         if (excess < 0 && n != _source) return false;
   480         _excess->set(n, excess);
   481       }
   482 
   483       typename Digraph::template NodeMap<bool> reached(_graph, false);
   484 
   485       _level->initStart();
   486       _level->initAddItem(_target);
   487 
   488       std::vector<Node> queue;
   489       reached.set(_source, true);
   490 
   491       queue.push_back(_target);
   492       reached.set(_target, true);
   493       while (!queue.empty()) {
   494         _level->initNewLevel();
   495         std::vector<Node> nqueue;
   496         for (int i = 0; i < int(queue.size()); ++i) {
   497           Node n = queue[i];
   498           for (InArcIt e(_graph, n); e != INVALID; ++e) {
   499             Node u = _graph.source(e);
   500             if (!reached[u] &&
   501                 _tolerance.positive((*_capacity)[e] - (*_flow)[e])) {
   502               reached.set(u, true);
   503               _level->initAddItem(u);
   504               nqueue.push_back(u);
   505             }
   506           }
   507           for (OutArcIt e(_graph, n); e != INVALID; ++e) {
   508             Node v = _graph.target(e);
   509             if (!reached[v] && _tolerance.positive((*_flow)[e])) {
   510               reached.set(v, true);
   511               _level->initAddItem(v);
   512               nqueue.push_back(v);
   513             }
   514           }
   515         }
   516         queue.swap(nqueue);
   517       }
   518       _level->initFinish();
   519 
   520       for (OutArcIt e(_graph, _source); e != INVALID; ++e) {
   521         Value rem = (*_capacity)[e] - (*_flow)[e];
   522         if (_tolerance.positive(rem)) {
   523           Node u = _graph.target(e);
   524           if ((*_level)[u] == _level->maxLevel()) continue;
   525           _flow->set(e, (*_capacity)[e]);
   526           _excess->set(u, (*_excess)[u] + rem);
   527           if (u != _target && !_level->active(u)) {
   528             _level->activate(u);
   529           }
   530         }
   531       }
   532       for (InArcIt e(_graph, _source); e != INVALID; ++e) {
   533         Value rem = (*_flow)[e];
   534         if (_tolerance.positive(rem)) {
   535           Node v = _graph.source(e);
   536           if ((*_level)[v] == _level->maxLevel()) continue;
   537           _flow->set(e, 0);
   538           _excess->set(v, (*_excess)[v] + rem);
   539           if (v != _target && !_level->active(v)) {
   540             _level->activate(v);
   541           }
   542         }
   543       }
   544       return true;
   545     }
   546 
   547     /// \brief Starts the first phase of the preflow algorithm.
   548     ///
   549     /// The preflow algorithm consists of two phases, this method runs
   550     /// the first phase. After the first phase the maximum flow value
   551     /// and a minimum value cut can already be computed, although a
   552     /// maximum flow is not yet obtained. So after calling this method
   553     /// \ref flowValue() returns the value of a maximum flow and \ref
   554     /// minCut() returns a minimum cut.
   555     /// \pre One of the \ref init() functions must be called before
   556     /// using this function.
   557     void startFirstPhase() {
   558       _phase = true;
   559 
   560       Node n = _level->highestActive();
   561       int level = _level->highestActiveLevel();
   562       while (n != INVALID) {
   563         int num = _node_num;
   564 
   565         while (num > 0 && n != INVALID) {
   566           Value excess = (*_excess)[n];
   567           int new_level = _level->maxLevel();
   568 
   569           for (OutArcIt e(_graph, n); e != INVALID; ++e) {
   570             Value rem = (*_capacity)[e] - (*_flow)[e];
   571             if (!_tolerance.positive(rem)) continue;
   572             Node v = _graph.target(e);
   573             if ((*_level)[v] < level) {
   574               if (!_level->active(v) && v != _target) {
   575                 _level->activate(v);
   576               }
   577               if (!_tolerance.less(rem, excess)) {
   578                 _flow->set(e, (*_flow)[e] + excess);
   579                 _excess->set(v, (*_excess)[v] + excess);
   580                 excess = 0;
   581                 goto no_more_push_1;
   582               } else {
   583                 excess -= rem;
   584                 _excess->set(v, (*_excess)[v] + rem);
   585                 _flow->set(e, (*_capacity)[e]);
   586               }
   587             } else if (new_level > (*_level)[v]) {
   588               new_level = (*_level)[v];
   589             }
   590           }
   591 
   592           for (InArcIt e(_graph, n); e != INVALID; ++e) {
   593             Value rem = (*_flow)[e];
   594             if (!_tolerance.positive(rem)) continue;
   595             Node v = _graph.source(e);
   596             if ((*_level)[v] < level) {
   597               if (!_level->active(v) && v != _target) {
   598                 _level->activate(v);
   599               }
   600               if (!_tolerance.less(rem, excess)) {
   601                 _flow->set(e, (*_flow)[e] - excess);
   602                 _excess->set(v, (*_excess)[v] + excess);
   603                 excess = 0;
   604                 goto no_more_push_1;
   605               } else {
   606                 excess -= rem;
   607                 _excess->set(v, (*_excess)[v] + rem);
   608                 _flow->set(e, 0);
   609               }
   610             } else if (new_level > (*_level)[v]) {
   611               new_level = (*_level)[v];
   612             }
   613           }
   614 
   615         no_more_push_1:
   616 
   617           _excess->set(n, excess);
   618 
   619           if (excess != 0) {
   620             if (new_level + 1 < _level->maxLevel()) {
   621               _level->liftHighestActive(new_level + 1);
   622             } else {
   623               _level->liftHighestActiveToTop();
   624             }
   625             if (_level->emptyLevel(level)) {
   626               _level->liftToTop(level);
   627             }
   628           } else {
   629             _level->deactivate(n);
   630           }
   631 
   632           n = _level->highestActive();
   633           level = _level->highestActiveLevel();
   634           --num;
   635         }
   636 
   637         num = _node_num * 20;
   638         while (num > 0 && n != INVALID) {
   639           Value excess = (*_excess)[n];
   640           int new_level = _level->maxLevel();
   641 
   642           for (OutArcIt e(_graph, n); e != INVALID; ++e) {
   643             Value rem = (*_capacity)[e] - (*_flow)[e];
   644             if (!_tolerance.positive(rem)) continue;
   645             Node v = _graph.target(e);
   646             if ((*_level)[v] < level) {
   647               if (!_level->active(v) && v != _target) {
   648                 _level->activate(v);
   649               }
   650               if (!_tolerance.less(rem, excess)) {
   651                 _flow->set(e, (*_flow)[e] + excess);
   652                 _excess->set(v, (*_excess)[v] + excess);
   653                 excess = 0;
   654                 goto no_more_push_2;
   655               } else {
   656                 excess -= rem;
   657                 _excess->set(v, (*_excess)[v] + rem);
   658                 _flow->set(e, (*_capacity)[e]);
   659               }
   660             } else if (new_level > (*_level)[v]) {
   661               new_level = (*_level)[v];
   662             }
   663           }
   664 
   665           for (InArcIt e(_graph, n); e != INVALID; ++e) {
   666             Value rem = (*_flow)[e];
   667             if (!_tolerance.positive(rem)) continue;
   668             Node v = _graph.source(e);
   669             if ((*_level)[v] < level) {
   670               if (!_level->active(v) && v != _target) {
   671                 _level->activate(v);
   672               }
   673               if (!_tolerance.less(rem, excess)) {
   674                 _flow->set(e, (*_flow)[e] - excess);
   675                 _excess->set(v, (*_excess)[v] + excess);
   676                 excess = 0;
   677                 goto no_more_push_2;
   678               } else {
   679                 excess -= rem;
   680                 _excess->set(v, (*_excess)[v] + rem);
   681                 _flow->set(e, 0);
   682               }
   683             } else if (new_level > (*_level)[v]) {
   684               new_level = (*_level)[v];
   685             }
   686           }
   687 
   688         no_more_push_2:
   689 
   690           _excess->set(n, excess);
   691 
   692           if (excess != 0) {
   693             if (new_level + 1 < _level->maxLevel()) {
   694               _level->liftActiveOn(level, new_level + 1);
   695             } else {
   696               _level->liftActiveToTop(level);
   697             }
   698             if (_level->emptyLevel(level)) {
   699               _level->liftToTop(level);
   700             }
   701           } else {
   702             _level->deactivate(n);
   703           }
   704 
   705           while (level >= 0 && _level->activeFree(level)) {
   706             --level;
   707           }
   708           if (level == -1) {
   709             n = _level->highestActive();
   710             level = _level->highestActiveLevel();
   711           } else {
   712             n = _level->activeOn(level);
   713           }
   714           --num;
   715         }
   716       }
   717     }
   718 
   719     /// \brief Starts the second phase of the preflow algorithm.
   720     ///
   721     /// The preflow algorithm consists of two phases, this method runs
   722     /// the second phase. After calling one of the \ref init() functions
   723     /// and \ref startFirstPhase() and then \ref startSecondPhase(),
   724     /// \ref flowMap() returns a maximum flow, \ref flowValue() returns the
   725     /// value of a maximum flow, \ref minCut() returns a minimum cut
   726     /// \pre One of the \ref init() functions and \ref startFirstPhase()
   727     /// must be called before using this function.
   728     void startSecondPhase() {
   729       _phase = false;
   730 
   731       typename Digraph::template NodeMap<bool> reached(_graph);
   732       for (NodeIt n(_graph); n != INVALID; ++n) {
   733         reached.set(n, (*_level)[n] < _level->maxLevel());
   734       }
   735 
   736       _level->initStart();
   737       _level->initAddItem(_source);
   738 
   739       std::vector<Node> queue;
   740       queue.push_back(_source);
   741       reached.set(_source, true);
   742 
   743       while (!queue.empty()) {
   744         _level->initNewLevel();
   745         std::vector<Node> nqueue;
   746         for (int i = 0; i < int(queue.size()); ++i) {
   747           Node n = queue[i];
   748           for (OutArcIt e(_graph, n); e != INVALID; ++e) {
   749             Node v = _graph.target(e);
   750             if (!reached[v] && _tolerance.positive((*_flow)[e])) {
   751               reached.set(v, true);
   752               _level->initAddItem(v);
   753               nqueue.push_back(v);
   754             }
   755           }
   756           for (InArcIt e(_graph, n); e != INVALID; ++e) {
   757             Node u = _graph.source(e);
   758             if (!reached[u] &&
   759                 _tolerance.positive((*_capacity)[e] - (*_flow)[e])) {
   760               reached.set(u, true);
   761               _level->initAddItem(u);
   762               nqueue.push_back(u);
   763             }
   764           }
   765         }
   766         queue.swap(nqueue);
   767       }
   768       _level->initFinish();
   769 
   770       for (NodeIt n(_graph); n != INVALID; ++n) {
   771         if (!reached[n]) {
   772           _level->dirtyTopButOne(n);
   773         } else if ((*_excess)[n] > 0 && _target != n) {
   774           _level->activate(n);
   775         }
   776       }
   777 
   778       Node n;
   779       while ((n = _level->highestActive()) != INVALID) {
   780         Value excess = (*_excess)[n];
   781         int level = _level->highestActiveLevel();
   782         int new_level = _level->maxLevel();
   783 
   784         for (OutArcIt e(_graph, n); e != INVALID; ++e) {
   785           Value rem = (*_capacity)[e] - (*_flow)[e];
   786           if (!_tolerance.positive(rem)) continue;
   787           Node v = _graph.target(e);
   788           if ((*_level)[v] < level) {
   789             if (!_level->active(v) && v != _source) {
   790               _level->activate(v);
   791             }
   792             if (!_tolerance.less(rem, excess)) {
   793               _flow->set(e, (*_flow)[e] + excess);
   794               _excess->set(v, (*_excess)[v] + excess);
   795               excess = 0;
   796               goto no_more_push;
   797             } else {
   798               excess -= rem;
   799               _excess->set(v, (*_excess)[v] + rem);
   800               _flow->set(e, (*_capacity)[e]);
   801             }
   802           } else if (new_level > (*_level)[v]) {
   803             new_level = (*_level)[v];
   804           }
   805         }
   806 
   807         for (InArcIt e(_graph, n); e != INVALID; ++e) {
   808           Value rem = (*_flow)[e];
   809           if (!_tolerance.positive(rem)) continue;
   810           Node v = _graph.source(e);
   811           if ((*_level)[v] < level) {
   812             if (!_level->active(v) && v != _source) {
   813               _level->activate(v);
   814             }
   815             if (!_tolerance.less(rem, excess)) {
   816               _flow->set(e, (*_flow)[e] - excess);
   817               _excess->set(v, (*_excess)[v] + excess);
   818               excess = 0;
   819               goto no_more_push;
   820             } else {
   821               excess -= rem;
   822               _excess->set(v, (*_excess)[v] + rem);
   823               _flow->set(e, 0);
   824             }
   825           } else if (new_level > (*_level)[v]) {
   826             new_level = (*_level)[v];
   827           }
   828         }
   829 
   830       no_more_push:
   831 
   832         _excess->set(n, excess);
   833 
   834         if (excess != 0) {
   835           if (new_level + 1 < _level->maxLevel()) {
   836             _level->liftHighestActive(new_level + 1);
   837           } else {
   838             // Calculation error
   839             _level->liftHighestActiveToTop();
   840           }
   841           if (_level->emptyLevel(level)) {
   842             // Calculation error
   843             _level->liftToTop(level);
   844           }
   845         } else {
   846           _level->deactivate(n);
   847         }
   848 
   849       }
   850     }
   851 
   852     /// \brief Runs the preflow algorithm.
   853     ///
   854     /// Runs the preflow algorithm.
   855     /// \note pf.run() is just a shortcut of the following code.
   856     /// \code
   857     ///   pf.init();
   858     ///   pf.startFirstPhase();
   859     ///   pf.startSecondPhase();
   860     /// \endcode
   861     void run() {
   862       init();
   863       startFirstPhase();
   864       startSecondPhase();
   865     }
   866 
   867     /// \brief Runs the preflow algorithm to compute the minimum cut.
   868     ///
   869     /// Runs the preflow algorithm to compute the minimum cut.
   870     /// \note pf.runMinCut() is just a shortcut of the following code.
   871     /// \code
   872     ///   pf.init();
   873     ///   pf.startFirstPhase();
   874     /// \endcode
   875     void runMinCut() {
   876       init();
   877       startFirstPhase();
   878     }
   879 
   880     /// @}
   881 
   882     /// \name Query Functions
   883     /// The results of the preflow algorithm can be obtained using these
   884     /// functions.\n
   885     /// Either one of the \ref run() "run*()" functions or one of the
   886     /// \ref startFirstPhase() "start*()" functions should be called
   887     /// before using them.
   888 
   889     ///@{
   890 
   891     /// \brief Returns the value of the maximum flow.
   892     ///
   893     /// Returns the value of the maximum flow by returning the excess
   894     /// of the target node. This value equals to the value of
   895     /// the maximum flow already after the first phase of the algorithm.
   896     ///
   897     /// \pre Either \ref run() or \ref init() must be called before
   898     /// using this function.
   899     Value flowValue() const {
   900       return (*_excess)[_target];
   901     }
   902 
   903     /// \brief Returns the flow on the given arc.
   904     ///
   905     /// Returns the flow on the given arc. This method can
   906     /// be called after the second phase of the algorithm.
   907     ///
   908     /// \pre Either \ref run() or \ref init() must be called before
   909     /// using this function.
   910     Value flow(const Arc& arc) const {
   911       return (*_flow)[arc];
   912     }
   913 
   914     /// \brief Returns a const reference to the flow map.
   915     ///
   916     /// Returns a const reference to the arc map storing the found flow.
   917     /// This method can be called after the second phase of the algorithm.
   918     ///
   919     /// \pre Either \ref run() or \ref init() must be called before
   920     /// using this function.
   921     const FlowMap& flowMap() const {
   922       return *_flow;
   923     }
   924 
   925     /// \brief Returns \c true when the node is on the source side of the
   926     /// minimum cut.
   927     ///
   928     /// Returns true when the node is on the source side of the found
   929     /// minimum cut. This method can be called both after running \ref
   930     /// startFirstPhase() and \ref startSecondPhase().
   931     ///
   932     /// \pre Either \ref run() or \ref init() must be called before
   933     /// using this function.
   934     bool minCut(const Node& node) const {
   935       return ((*_level)[node] == _level->maxLevel()) == _phase;
   936     }
   937 
   938     /// \brief Gives back a minimum value cut.
   939     ///
   940     /// Sets \c cutMap to the characteristic vector of a minimum value
   941     /// cut. \c cutMap should be a \ref concepts::WriteMap "writable"
   942     /// node map with \c bool (or convertible) value type.
   943     ///
   944     /// This method can be called both after running \ref startFirstPhase()
   945     /// and \ref startSecondPhase(). The result after the second phase
   946     /// could be slightly different if inexact computation is used.
   947     ///
   948     /// \note This function calls \ref minCut() for each node, so it runs in
   949     /// \f$O(n)\f$ time.
   950     ///
   951     /// \pre Either \ref run() or \ref init() must be called before
   952     /// using this function.
   953     template <typename CutMap>
   954     void minCutMap(CutMap& cutMap) const {
   955       for (NodeIt n(_graph); n != INVALID; ++n) {
   956         cutMap.set(n, minCut(n));
   957       }
   958     }
   959 
   960     /// @}
   961   };
   962 }
   963 
   964 #endif