1 /* -*- mode: C++; indent-tabs-mode: nil; -*-
3 * This file is a part of LEMON, a generic C++ optimization library.
5 * Copyright (C) 2003-2009
6 * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
7 * (Egervary Research Group on Combinatorial Optimization, EGRES).
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.
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
19 #ifndef LEMON_PREFLOW_H
20 #define LEMON_PREFLOW_H
22 #include <lemon/tolerance.h>
23 #include <lemon/elevator.h>
27 /// \brief Implementation of the preflow algorithm.
31 /// \brief Default traits class of Preflow class.
33 /// Default traits class of Preflow class.
34 /// \tparam GR Digraph type.
35 /// \tparam CAP Capacity map type.
36 template <typename GR, typename CAP>
37 struct PreflowDefaultTraits {
39 /// \brief The type of the digraph the algorithm runs on.
42 /// \brief The type of the map that stores the arc capacities.
44 /// The type of the map that stores the arc capacities.
45 /// It must meet the \ref concepts::ReadMap "ReadMap" concept.
46 typedef CAP CapacityMap;
48 /// \brief The type of the flow values.
49 typedef typename CapacityMap::Value Value;
51 /// \brief The type of the map that stores the flow values.
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;
57 /// \brief Instantiates a FlowMap.
59 /// This function instantiates a \ref FlowMap.
60 /// \param digraph The digraph for which we would like to define
62 static FlowMap* createFlowMap(const Digraph& digraph) {
63 return new FlowMap(digraph);
66 /// \brief The elevator type used by Preflow algorithm.
68 /// The elevator type used by Preflow algorithm.
71 /// \sa LinkedElevator
72 typedef LinkedElevator<Digraph, typename Digraph::Node> Elevator;
74 /// \brief Instantiates an Elevator.
76 /// This function instantiates an \ref Elevator.
77 /// \param digraph The digraph for which we would like to define
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);
84 /// \brief The tolerance used by the algorithm
86 /// The tolerance used by the algorithm to handle inexact computation.
87 typedef lemon::Tolerance<Value> Tolerance;
94 /// \brief %Preflow algorithm class.
96 /// This class provides an implementation of Goldberg-Tarjan's \e preflow
97 /// \e push-relabel algorithm producing a \ref max_flow
98 /// "flow of maximum value" in a digraph.
99 /// The preflow algorithms are the fastest known maximum
100 /// flow algorithms. The current implementation use a mixture of the
101 /// \e "highest label" and the \e "bound decrease" heuristics.
102 /// The worst case time complexity of the algorithm is \f$O(n^2\sqrt{e})\f$.
104 /// The algorithm consists of two phases. After the first phase
105 /// the maximum flow value and the minimum cut is obtained. The
106 /// second phase constructs a feasible maximum flow on each arc.
108 /// \tparam GR The type of the digraph the algorithm runs on.
109 /// \tparam CAP The type of the capacity map. The default map
110 /// type is \ref concepts::Digraph::ArcMap "GR::ArcMap<int>".
112 template <typename GR, typename CAP, typename TR>
114 template <typename GR,
115 typename CAP = typename GR::template ArcMap<int>,
116 typename TR = PreflowDefaultTraits<GR, CAP> >
121 ///The \ref PreflowDefaultTraits "traits class" of the algorithm.
123 ///The type of the digraph the algorithm runs on.
124 typedef typename Traits::Digraph Digraph;
125 ///The type of the capacity map.
126 typedef typename Traits::CapacityMap CapacityMap;
127 ///The type of the flow values.
128 typedef typename Traits::Value Value;
130 ///The type of the flow map.
131 typedef typename Traits::FlowMap FlowMap;
132 ///The type of the elevator.
133 typedef typename Traits::Elevator Elevator;
134 ///The type of the tolerance.
135 typedef typename Traits::Tolerance Tolerance;
139 TEMPLATE_DIGRAPH_TYPEDEFS(Digraph);
141 const Digraph& _graph;
142 const CapacityMap* _capacity;
146 Node _source, _target;
154 typedef typename Digraph::template NodeMap<Value> ExcessMap;
157 Tolerance _tolerance;
162 void createStructures() {
163 _node_num = countNodes(_graph);
166 _flow = Traits::createFlowMap(_graph);
170 _level = Traits::createElevator(_graph, _node_num);
174 _excess = new ExcessMap(_graph);
178 void destroyStructures() {
192 typedef Preflow Create;
194 ///\name Named Template Parameters
198 template <typename T>
199 struct SetFlowMapTraits : public Traits {
201 static FlowMap *createFlowMap(const Digraph&) {
202 LEMON_ASSERT(false, "FlowMap is not initialized");
203 return 0; // ignore warnings
207 /// \brief \ref named-templ-param "Named parameter" for setting
210 /// \ref named-templ-param "Named parameter" for setting FlowMap
212 template <typename T>
214 : public Preflow<Digraph, CapacityMap, SetFlowMapTraits<T> > {
215 typedef Preflow<Digraph, CapacityMap,
216 SetFlowMapTraits<T> > Create;
219 template <typename T>
220 struct SetElevatorTraits : public Traits {
222 static Elevator *createElevator(const Digraph&, int) {
223 LEMON_ASSERT(false, "Elevator is not initialized");
224 return 0; // ignore warnings
228 /// \brief \ref named-templ-param "Named parameter" for setting
231 /// \ref named-templ-param "Named parameter" for setting Elevator
232 /// type. If this named parameter is used, then an external
233 /// elevator object must be passed to the algorithm using the
234 /// \ref elevator(Elevator&) "elevator()" function before calling
235 /// \ref run() or \ref init().
236 /// \sa SetStandardElevator
237 template <typename T>
239 : public Preflow<Digraph, CapacityMap, SetElevatorTraits<T> > {
240 typedef Preflow<Digraph, CapacityMap,
241 SetElevatorTraits<T> > Create;
244 template <typename T>
245 struct SetStandardElevatorTraits : public Traits {
247 static Elevator *createElevator(const Digraph& digraph, int max_level) {
248 return new Elevator(digraph, max_level);
252 /// \brief \ref named-templ-param "Named parameter" for setting
253 /// Elevator type with automatic allocation
255 /// \ref named-templ-param "Named parameter" for setting Elevator
256 /// type with automatic allocation.
257 /// The Elevator should have standard constructor interface to be
258 /// able to automatically created by the algorithm (i.e. the
259 /// digraph and the maximum level should be passed to it).
260 /// However an external elevator object could also be passed to the
261 /// algorithm with the \ref elevator(Elevator&) "elevator()" function
262 /// before calling \ref run() or \ref init().
264 template <typename T>
265 struct SetStandardElevator
266 : public Preflow<Digraph, CapacityMap,
267 SetStandardElevatorTraits<T> > {
268 typedef Preflow<Digraph, CapacityMap,
269 SetStandardElevatorTraits<T> > Create;
281 /// \brief The constructor of the class.
283 /// The constructor of the class.
284 /// \param digraph The digraph the algorithm runs on.
285 /// \param capacity The capacity of the arcs.
286 /// \param source The source node.
287 /// \param target The target node.
288 Preflow(const Digraph& digraph, const CapacityMap& capacity,
289 Node source, Node target)
290 : _graph(digraph), _capacity(&capacity),
291 _node_num(0), _source(source), _target(target),
292 _flow(0), _local_flow(false),
293 _level(0), _local_level(false),
294 _excess(0), _tolerance(), _phase() {}
296 /// \brief Destructor.
303 /// \brief Sets the capacity map.
305 /// Sets the capacity map.
306 /// \return <tt>(*this)</tt>
307 Preflow& capacityMap(const CapacityMap& map) {
312 /// \brief Sets the flow map.
314 /// Sets the flow map.
315 /// If you don't use this function before calling \ref run() or
316 /// \ref init(), an instance will be allocated automatically.
317 /// The destructor deallocates this automatically allocated map,
319 /// \return <tt>(*this)</tt>
320 Preflow& flowMap(FlowMap& map) {
329 /// \brief Sets the source node.
331 /// Sets the source node.
332 /// \return <tt>(*this)</tt>
333 Preflow& source(const Node& node) {
338 /// \brief Sets the target node.
340 /// Sets the target node.
341 /// \return <tt>(*this)</tt>
342 Preflow& target(const Node& node) {
347 /// \brief Sets the elevator used by algorithm.
349 /// Sets the elevator used by algorithm.
350 /// If you don't use this function before calling \ref run() or
351 /// \ref init(), an instance will be allocated automatically.
352 /// The destructor deallocates this automatically allocated elevator,
354 /// \return <tt>(*this)</tt>
355 Preflow& elevator(Elevator& elevator) {
358 _local_level = false;
364 /// \brief Returns a const reference to the elevator.
366 /// Returns a const reference to the elevator.
368 /// \pre Either \ref run() or \ref init() must be called before
369 /// using this function.
370 const Elevator& elevator() const {
374 /// \brief Sets the tolerance used by algorithm.
376 /// Sets the tolerance used by algorithm.
377 Preflow& tolerance(const Tolerance& tolerance) {
378 _tolerance = tolerance;
382 /// \brief Returns a const reference to the tolerance.
384 /// Returns a const reference to the tolerance.
385 const Tolerance& tolerance() const {
389 /// \name Execution Control
390 /// The simplest way to execute the preflow algorithm is to use
391 /// \ref run() or \ref runMinCut().\n
392 /// If you need more control on the initial solution or the execution,
393 /// first you have to call one of the \ref init() functions, then
394 /// \ref startFirstPhase() and if you need it \ref startSecondPhase().
398 /// \brief Initializes the internal data structures.
400 /// Initializes the internal data structures and sets the initial
401 /// flow to zero on each arc.
406 for (NodeIt n(_graph); n != INVALID; ++n) {
410 for (ArcIt e(_graph); e != INVALID; ++e) {
414 typename Digraph::template NodeMap<bool> reached(_graph, false);
417 _level->initAddItem(_target);
419 std::vector<Node> queue;
420 reached[_source] = true;
422 queue.push_back(_target);
423 reached[_target] = true;
424 while (!queue.empty()) {
425 _level->initNewLevel();
426 std::vector<Node> nqueue;
427 for (int i = 0; i < int(queue.size()); ++i) {
429 for (InArcIt e(_graph, n); e != INVALID; ++e) {
430 Node u = _graph.source(e);
431 if (!reached[u] && _tolerance.positive((*_capacity)[e])) {
433 _level->initAddItem(u);
440 _level->initFinish();
442 for (OutArcIt e(_graph, _source); e != INVALID; ++e) {
443 if (_tolerance.positive((*_capacity)[e])) {
444 Node u = _graph.target(e);
445 if ((*_level)[u] == _level->maxLevel()) continue;
446 _flow->set(e, (*_capacity)[e]);
447 (*_excess)[u] += (*_capacity)[e];
448 if (u != _target && !_level->active(u)) {
455 /// \brief Initializes the internal data structures using the
458 /// Initializes the internal data structures and sets the initial
459 /// flow to the given \c flowMap. The \c flowMap should contain a
460 /// flow or at least a preflow, i.e. at each node excluding the
461 /// source node the incoming flow should greater or equal to the
463 /// \return \c false if the given \c flowMap is not a preflow.
464 template <typename FlowMap>
465 bool init(const FlowMap& flowMap) {
468 for (ArcIt e(_graph); e != INVALID; ++e) {
469 _flow->set(e, flowMap[e]);
472 for (NodeIt n(_graph); n != INVALID; ++n) {
474 for (InArcIt e(_graph, n); e != INVALID; ++e) {
475 excess += (*_flow)[e];
477 for (OutArcIt e(_graph, n); e != INVALID; ++e) {
478 excess -= (*_flow)[e];
480 if (excess < 0 && n != _source) return false;
481 (*_excess)[n] = excess;
484 typename Digraph::template NodeMap<bool> reached(_graph, false);
487 _level->initAddItem(_target);
489 std::vector<Node> queue;
490 reached[_source] = true;
492 queue.push_back(_target);
493 reached[_target] = true;
494 while (!queue.empty()) {
495 _level->initNewLevel();
496 std::vector<Node> nqueue;
497 for (int i = 0; i < int(queue.size()); ++i) {
499 for (InArcIt e(_graph, n); e != INVALID; ++e) {
500 Node u = _graph.source(e);
502 _tolerance.positive((*_capacity)[e] - (*_flow)[e])) {
504 _level->initAddItem(u);
508 for (OutArcIt e(_graph, n); e != INVALID; ++e) {
509 Node v = _graph.target(e);
510 if (!reached[v] && _tolerance.positive((*_flow)[e])) {
512 _level->initAddItem(v);
519 _level->initFinish();
521 for (OutArcIt e(_graph, _source); e != INVALID; ++e) {
522 Value rem = (*_capacity)[e] - (*_flow)[e];
523 if (_tolerance.positive(rem)) {
524 Node u = _graph.target(e);
525 if ((*_level)[u] == _level->maxLevel()) continue;
526 _flow->set(e, (*_capacity)[e]);
527 (*_excess)[u] += rem;
530 for (InArcIt e(_graph, _source); e != INVALID; ++e) {
531 Value rem = (*_flow)[e];
532 if (_tolerance.positive(rem)) {
533 Node v = _graph.source(e);
534 if ((*_level)[v] == _level->maxLevel()) continue;
536 (*_excess)[v] += rem;
539 for (NodeIt n(_graph); n != INVALID; ++n)
540 if(n!=_source && n!=_target && _tolerance.positive((*_excess)[n]))
546 /// \brief Starts the first phase of the preflow algorithm.
548 /// The preflow algorithm consists of two phases, this method runs
549 /// the first phase. After the first phase the maximum flow value
550 /// and a minimum value cut can already be computed, although a
551 /// maximum flow is not yet obtained. So after calling this method
552 /// \ref flowValue() returns the value of a maximum flow and \ref
553 /// minCut() returns a minimum cut.
554 /// \pre One of the \ref init() functions must be called before
555 /// using this function.
556 void startFirstPhase() {
566 n = _level->highestActive();
567 if (n == INVALID) goto first_phase_done;
568 level = _level->highestActiveLevel();
571 Value excess = (*_excess)[n];
572 int new_level = _level->maxLevel();
574 for (OutArcIt e(_graph, n); e != INVALID; ++e) {
575 Value rem = (*_capacity)[e] - (*_flow)[e];
576 if (!_tolerance.positive(rem)) continue;
577 Node v = _graph.target(e);
578 if ((*_level)[v] < level) {
579 if (!_level->active(v) && v != _target) {
582 if (!_tolerance.less(rem, excess)) {
583 _flow->set(e, (*_flow)[e] + excess);
584 (*_excess)[v] += excess;
589 (*_excess)[v] += rem;
590 _flow->set(e, (*_capacity)[e]);
592 } else if (new_level > (*_level)[v]) {
593 new_level = (*_level)[v];
597 for (InArcIt e(_graph, n); e != INVALID; ++e) {
598 Value rem = (*_flow)[e];
599 if (!_tolerance.positive(rem)) continue;
600 Node v = _graph.source(e);
601 if ((*_level)[v] < level) {
602 if (!_level->active(v) && v != _target) {
605 if (!_tolerance.less(rem, excess)) {
606 _flow->set(e, (*_flow)[e] - excess);
607 (*_excess)[v] += excess;
612 (*_excess)[v] += rem;
615 } else if (new_level > (*_level)[v]) {
616 new_level = (*_level)[v];
622 (*_excess)[n] = excess;
625 if (new_level + 1 < _level->maxLevel()) {
626 _level->liftHighestActive(new_level + 1);
628 _level->liftHighestActiveToTop();
630 if (_level->emptyLevel(level)) {
631 _level->liftToTop(level);
634 _level->deactivate(n);
638 num = _node_num * 20;
640 while (level >= 0 && _level->activeFree(level)) {
644 n = _level->highestActive();
645 level = _level->highestActiveLevel();
646 if (n == INVALID) goto first_phase_done;
648 n = _level->activeOn(level);
652 Value excess = (*_excess)[n];
653 int new_level = _level->maxLevel();
655 for (OutArcIt e(_graph, n); e != INVALID; ++e) {
656 Value rem = (*_capacity)[e] - (*_flow)[e];
657 if (!_tolerance.positive(rem)) continue;
658 Node v = _graph.target(e);
659 if ((*_level)[v] < level) {
660 if (!_level->active(v) && v != _target) {
663 if (!_tolerance.less(rem, excess)) {
664 _flow->set(e, (*_flow)[e] + excess);
665 (*_excess)[v] += excess;
670 (*_excess)[v] += rem;
671 _flow->set(e, (*_capacity)[e]);
673 } else if (new_level > (*_level)[v]) {
674 new_level = (*_level)[v];
678 for (InArcIt e(_graph, n); e != INVALID; ++e) {
679 Value rem = (*_flow)[e];
680 if (!_tolerance.positive(rem)) continue;
681 Node v = _graph.source(e);
682 if ((*_level)[v] < level) {
683 if (!_level->active(v) && v != _target) {
686 if (!_tolerance.less(rem, excess)) {
687 _flow->set(e, (*_flow)[e] - excess);
688 (*_excess)[v] += excess;
693 (*_excess)[v] += rem;
696 } else if (new_level > (*_level)[v]) {
697 new_level = (*_level)[v];
703 (*_excess)[n] = excess;
706 if (new_level + 1 < _level->maxLevel()) {
707 _level->liftActiveOn(level, new_level + 1);
709 _level->liftActiveToTop(level);
711 if (_level->emptyLevel(level)) {
712 _level->liftToTop(level);
715 _level->deactivate(n);
722 /// \brief Starts the second phase of the preflow algorithm.
724 /// The preflow algorithm consists of two phases, this method runs
725 /// the second phase. After calling one of the \ref init() functions
726 /// and \ref startFirstPhase() and then \ref startSecondPhase(),
727 /// \ref flowMap() returns a maximum flow, \ref flowValue() returns the
728 /// value of a maximum flow, \ref minCut() returns a minimum cut
729 /// \pre One of the \ref init() functions and \ref startFirstPhase()
730 /// must be called before using this function.
731 void startSecondPhase() {
734 typename Digraph::template NodeMap<bool> reached(_graph);
735 for (NodeIt n(_graph); n != INVALID; ++n) {
736 reached[n] = (*_level)[n] < _level->maxLevel();
740 _level->initAddItem(_source);
742 std::vector<Node> queue;
743 queue.push_back(_source);
744 reached[_source] = true;
746 while (!queue.empty()) {
747 _level->initNewLevel();
748 std::vector<Node> nqueue;
749 for (int i = 0; i < int(queue.size()); ++i) {
751 for (OutArcIt e(_graph, n); e != INVALID; ++e) {
752 Node v = _graph.target(e);
753 if (!reached[v] && _tolerance.positive((*_flow)[e])) {
755 _level->initAddItem(v);
759 for (InArcIt e(_graph, n); e != INVALID; ++e) {
760 Node u = _graph.source(e);
762 _tolerance.positive((*_capacity)[e] - (*_flow)[e])) {
764 _level->initAddItem(u);
771 _level->initFinish();
773 for (NodeIt n(_graph); n != INVALID; ++n) {
775 _level->dirtyTopButOne(n);
776 } else if ((*_excess)[n] > 0 && _target != n) {
782 while ((n = _level->highestActive()) != INVALID) {
783 Value excess = (*_excess)[n];
784 int level = _level->highestActiveLevel();
785 int new_level = _level->maxLevel();
787 for (OutArcIt e(_graph, n); e != INVALID; ++e) {
788 Value rem = (*_capacity)[e] - (*_flow)[e];
789 if (!_tolerance.positive(rem)) continue;
790 Node v = _graph.target(e);
791 if ((*_level)[v] < level) {
792 if (!_level->active(v) && v != _source) {
795 if (!_tolerance.less(rem, excess)) {
796 _flow->set(e, (*_flow)[e] + excess);
797 (*_excess)[v] += excess;
802 (*_excess)[v] += rem;
803 _flow->set(e, (*_capacity)[e]);
805 } else if (new_level > (*_level)[v]) {
806 new_level = (*_level)[v];
810 for (InArcIt e(_graph, n); e != INVALID; ++e) {
811 Value rem = (*_flow)[e];
812 if (!_tolerance.positive(rem)) continue;
813 Node v = _graph.source(e);
814 if ((*_level)[v] < level) {
815 if (!_level->active(v) && v != _source) {
818 if (!_tolerance.less(rem, excess)) {
819 _flow->set(e, (*_flow)[e] - excess);
820 (*_excess)[v] += excess;
825 (*_excess)[v] += rem;
828 } else if (new_level > (*_level)[v]) {
829 new_level = (*_level)[v];
835 (*_excess)[n] = excess;
838 if (new_level + 1 < _level->maxLevel()) {
839 _level->liftHighestActive(new_level + 1);
842 _level->liftHighestActiveToTop();
844 if (_level->emptyLevel(level)) {
846 _level->liftToTop(level);
849 _level->deactivate(n);
855 /// \brief Runs the preflow algorithm.
857 /// Runs the preflow algorithm.
858 /// \note pf.run() is just a shortcut of the following code.
861 /// pf.startFirstPhase();
862 /// pf.startSecondPhase();
870 /// \brief Runs the preflow algorithm to compute the minimum cut.
872 /// Runs the preflow algorithm to compute the minimum cut.
873 /// \note pf.runMinCut() is just a shortcut of the following code.
876 /// pf.startFirstPhase();
885 /// \name Query Functions
886 /// The results of the preflow algorithm can be obtained using these
888 /// Either one of the \ref run() "run*()" functions or one of the
889 /// \ref startFirstPhase() "start*()" functions should be called
890 /// before using them.
894 /// \brief Returns the value of the maximum flow.
896 /// Returns the value of the maximum flow by returning the excess
897 /// of the target node. This value equals to the value of
898 /// the maximum flow already after the first phase of the algorithm.
900 /// \pre Either \ref run() or \ref init() must be called before
901 /// using this function.
902 Value flowValue() const {
903 return (*_excess)[_target];
906 /// \brief Returns the flow value on the given arc.
908 /// Returns the flow value on the given arc. This method can
909 /// be called after the second phase of the algorithm.
911 /// \pre Either \ref run() or \ref init() must be called before
912 /// using this function.
913 Value flow(const Arc& arc) const {
914 return (*_flow)[arc];
917 /// \brief Returns a const reference to the flow map.
919 /// Returns a const reference to the arc map storing the found flow.
920 /// This method can be called after the second phase of the algorithm.
922 /// \pre Either \ref run() or \ref init() must be called before
923 /// using this function.
924 const FlowMap& flowMap() const {
928 /// \brief Returns \c true when the node is on the source side of the
931 /// Returns true when the node is on the source side of the found
932 /// minimum cut. This method can be called both after running \ref
933 /// startFirstPhase() and \ref startSecondPhase().
935 /// \pre Either \ref run() or \ref init() must be called before
936 /// using this function.
937 bool minCut(const Node& node) const {
938 return ((*_level)[node] == _level->maxLevel()) == _phase;
941 /// \brief Gives back a minimum value cut.
943 /// Sets \c cutMap to the characteristic vector of a minimum value
944 /// cut. \c cutMap should be a \ref concepts::WriteMap "writable"
945 /// node map with \c bool (or convertible) value type.
947 /// This method can be called both after running \ref startFirstPhase()
948 /// and \ref startSecondPhase(). The result after the second phase
949 /// could be slightly different if inexact computation is used.
951 /// \note This function calls \ref minCut() for each node, so it runs in
954 /// \pre Either \ref run() or \ref init() must be called before
955 /// using this function.
956 template <typename CutMap>
957 void minCutMap(CutMap& cutMap) const {
958 for (NodeIt n(_graph); n != INVALID; ++n) {
959 cutMap.set(n, minCut(n));