/* -*- mode: C++; indent-tabs-mode: nil; -*- * * This file is a part of LEMON, a generic C++ optimization library. * * Copyright (C) 2003-2013 * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport * (Egervary Research Group on Combinatorial Optimization, EGRES). * * Permission to use, modify and distribute this software is granted * provided that this copyright notice appears in all copies. For * precise terms see the accompanying LICENSE file. * * This software is provided "AS IS" with no warranty of any kind, * express or implied, and with no claim as to its suitability for any * purpose. * */ #ifndef LEMON_NAGAMOCHI_IBARAKI_H #define LEMON_NAGAMOCHI_IBARAKI_H /// \ingroup min_cut /// \file /// \brief Implementation of the Nagamochi-Ibaraki algorithm. #include #include #include #include #include #include #include namespace lemon { /// \brief Default traits class for NagamochiIbaraki class. /// /// Default traits class for NagamochiIbaraki class. /// \param GR The undirected graph type. /// \param CM Type of capacity map. template struct NagamochiIbarakiDefaultTraits { /// The type of the capacity map. typedef typename CM::Value Value; /// The undirected graph type the algorithm runs on. typedef GR Graph; /// \brief The type of the map that stores the edge capacities. /// /// The type of the map that stores the edge capacities. /// It must meet the \ref concepts::ReadMap "ReadMap" concept. typedef CM CapacityMap; /// \brief Instantiates a CapacityMap. /// /// This function instantiates a \ref CapacityMap. #ifdef DOXYGEN static CapacityMap *createCapacityMap(const Graph& graph) #else static CapacityMap *createCapacityMap(const Graph&) #endif { LEMON_ASSERT(false, "CapacityMap is not initialized"); return 0; // ignore warnings } /// \brief The cross reference type used by heap. /// /// The cross reference type used by heap. /// Usually \c Graph::NodeMap. typedef typename Graph::template NodeMap HeapCrossRef; /// \brief Instantiates a HeapCrossRef. /// /// This function instantiates a \ref HeapCrossRef. /// \param g is the graph, to which we would like to define the /// \ref HeapCrossRef. static HeapCrossRef *createHeapCrossRef(const Graph& g) { return new HeapCrossRef(g); } /// \brief The heap type used by NagamochiIbaraki algorithm. /// /// The heap type used by NagamochiIbaraki algorithm. It has to /// maximize the priorities. /// /// \sa BinHeap /// \sa NagamochiIbaraki typedef BinHeap > Heap; /// \brief Instantiates a Heap. /// /// This function instantiates a \ref Heap. /// \param r is the cross reference of the heap. static Heap *createHeap(HeapCrossRef& r) { return new Heap(r); } }; /// \ingroup min_cut /// /// \brief Calculates the minimum cut in an undirected graph. /// /// Calculates the minimum cut in an undirected graph with the /// Nagamochi-Ibaraki algorithm. The algorithm separates the graph's /// nodes into two partitions with the minimum sum of edge capacities /// between the two partitions. The algorithm can be used to test /// the network reliability, especially to test how many links have /// to be destroyed in the network to split it to at least two /// distinict subnetworks. /// /// The complexity of the algorithm is \f$ O(nm\log(n)) \f$ but with /// \ref FibHeap "Fibonacci heap" it can be decreased to /// \f$ O(nm+n^2\log(n)) \f$. When the edges have unit capacities, /// \c BucketHeap can be used which yields \f$ O(nm) \f$ time /// complexity. /// /// \warning The value type of the capacity map should be able to /// hold any cut value of the graph, otherwise the result can /// overflow. /// \note This capacity is supposed to be integer type. #ifdef DOXYGEN template #else template , typename TR = NagamochiIbarakiDefaultTraits > #endif class NagamochiIbaraki { public: typedef TR Traits; /// The type of the underlying graph. typedef typename Traits::Graph Graph; /// The type of the capacity map. typedef typename Traits::CapacityMap CapacityMap; /// The value type of the capacity map. typedef typename Traits::CapacityMap::Value Value; /// The heap type used by the algorithm. typedef typename Traits::Heap Heap; /// The cross reference type used for the heap. typedef typename Traits::HeapCrossRef HeapCrossRef; ///\name Named template parameters ///@{ struct SetUnitCapacityTraits : public Traits { typedef ConstMap > CapacityMap; static CapacityMap *createCapacityMap(const Graph&) { return new CapacityMap(); } }; /// \brief \ref named-templ-param "Named parameter" for setting /// the capacity map to a constMap() instance /// /// \ref named-templ-param "Named parameter" for setting /// the capacity map to a constMap() instance struct SetUnitCapacity : public NagamochiIbaraki { typedef NagamochiIbaraki Create; }; template struct SetHeapTraits : public Traits { typedef CR HeapCrossRef; typedef H Heap; static HeapCrossRef *createHeapCrossRef(int num) { LEMON_ASSERT(false, "HeapCrossRef is not initialized"); return 0; // ignore warnings } static Heap *createHeap(HeapCrossRef &) { LEMON_ASSERT(false, "Heap is not initialized"); return 0; // ignore warnings } }; /// \brief \ref named-templ-param "Named parameter" for setting /// heap and cross reference type /// /// \ref named-templ-param "Named parameter" for setting heap and /// cross reference type. The heap has to maximize the priorities. template > struct SetHeap : public NagamochiIbaraki > { typedef NagamochiIbaraki< Graph, CapacityMap, SetHeapTraits > Create; }; template struct SetStandardHeapTraits : public Traits { typedef CR HeapCrossRef; typedef H Heap; static HeapCrossRef *createHeapCrossRef(int size) { return new HeapCrossRef(size); } static Heap *createHeap(HeapCrossRef &crossref) { return new Heap(crossref); } }; /// \brief \ref named-templ-param "Named parameter" for setting /// heap and cross reference type with automatic allocation /// /// \ref named-templ-param "Named parameter" for setting heap and /// cross reference type with automatic allocation. They should /// have standard constructor interfaces to be able to /// automatically created by the algorithm (i.e. the graph should /// be passed to the constructor of the cross reference and the /// cross reference should be passed to the constructor of the /// heap). However, external heap and cross reference objects /// could also be passed to the algorithm using the \ref heap() /// function before calling \ref run() or \ref init(). The heap /// has to maximize the priorities. /// \sa SetHeap template > struct SetStandardHeap : public NagamochiIbaraki > { typedef NagamochiIbaraki > Create; }; ///@} private: const Graph &_graph; const CapacityMap *_capacity; bool _local_capacity; // unit capacity struct ArcData { typename Graph::Node target; int prev, next; }; struct EdgeData { Value capacity; Value cut; }; struct NodeData { int first_arc; typename Graph::Node prev, next; int curr_arc; typename Graph::Node last_rep; Value sum; }; typename Graph::template NodeMap *_nodes; std::vector _arcs; std::vector _edges; typename Graph::Node _first_node; int _node_num; Value _min_cut; HeapCrossRef *_heap_cross_ref; bool _local_heap_cross_ref; Heap *_heap; bool _local_heap; typedef typename Graph::template NodeMap NodeList; NodeList *_next_rep; typedef typename Graph::template NodeMap MinCutMap; MinCutMap *_cut_map; void createStructures() { if (!_nodes) { _nodes = new (typename Graph::template NodeMap)(_graph); } if (!_capacity) { _local_capacity = true; _capacity = Traits::createCapacityMap(_graph); } if (!_heap_cross_ref) { _local_heap_cross_ref = true; _heap_cross_ref = Traits::createHeapCrossRef(_graph); } if (!_heap) { _local_heap = true; _heap = Traits::createHeap(*_heap_cross_ref); } if (!_next_rep) { _next_rep = new NodeList(_graph); } if (!_cut_map) { _cut_map = new MinCutMap(_graph); } } protected: //This is here to avoid a gcc-3.3 compilation error. //It should never be called. NagamochiIbaraki() {} public: typedef NagamochiIbaraki Create; /// \brief Constructor. /// /// \param graph The graph the algorithm runs on. /// \param capacity The capacity map used by the algorithm. NagamochiIbaraki(const Graph& graph, const CapacityMap& capacity) : _graph(graph), _capacity(&capacity), _local_capacity(false), _nodes(0), _arcs(), _edges(), _min_cut(), _heap_cross_ref(0), _local_heap_cross_ref(false), _heap(0), _local_heap(false), _next_rep(0), _cut_map(0) {} /// \brief Constructor. /// /// This constructor can be used only when the Traits class /// defines how can the local capacity map be instantiated. /// If the SetUnitCapacity used the algorithm automatically /// constructs the capacity map. /// ///\param graph The graph the algorithm runs on. NagamochiIbaraki(const Graph& graph) : _graph(graph), _capacity(0), _local_capacity(false), _nodes(0), _arcs(), _edges(), _min_cut(), _heap_cross_ref(0), _local_heap_cross_ref(false), _heap(0), _local_heap(false), _next_rep(0), _cut_map(0) {} /// \brief Destructor. /// /// Destructor. ~NagamochiIbaraki() { if (_local_capacity) delete _capacity; if (_nodes) delete _nodes; if (_local_heap) delete _heap; if (_local_heap_cross_ref) delete _heap_cross_ref; if (_next_rep) delete _next_rep; if (_cut_map) delete _cut_map; } /// \brief Sets the heap and the cross reference used by algorithm. /// /// Sets the heap and the cross reference used by algorithm. /// If you don't use this function before calling \ref run(), /// it will allocate one. The destuctor deallocates this /// automatically allocated heap and cross reference, of course. /// \return (*this) NagamochiIbaraki &heap(Heap& hp, HeapCrossRef &cr) { if (_local_heap_cross_ref) { delete _heap_cross_ref; _local_heap_cross_ref = false; } _heap_cross_ref = &cr; if (_local_heap) { delete _heap; _local_heap = false; } _heap = &hp; return *this; } /// \name Execution control /// The simplest way to execute the algorithm is to use /// one of the member functions called \c run(). /// \n /// If you need more control on the execution, /// first you must call \ref init() and then call the start() /// or proper times the processNextPhase() member functions. ///@{ /// \brief Initializes the internal data structures. /// /// Initializes the internal data structures. void init() { createStructures(); int edge_num = countEdges(_graph); _edges.resize(edge_num); _arcs.resize(2 * edge_num); typename Graph::Node prev = INVALID; _node_num = 0; for (typename Graph::NodeIt n(_graph); n != INVALID; ++n) { (*_cut_map)[n] = false; (*_next_rep)[n] = INVALID; (*_nodes)[n].last_rep = n; (*_nodes)[n].first_arc = -1; (*_nodes)[n].curr_arc = -1; (*_nodes)[n].prev = prev; if (prev != INVALID) { (*_nodes)[prev].next = n; } (*_nodes)[n].next = INVALID; (*_nodes)[n].sum = 0; prev = n; ++_node_num; } _first_node = typename Graph::NodeIt(_graph); int index = 0; for (typename Graph::NodeIt n(_graph); n != INVALID; ++n) { for (typename Graph::OutArcIt a(_graph, n); a != INVALID; ++a) { typename Graph::Node m = _graph.target(a); if (!(n < m)) continue; (*_nodes)[n].sum += (*_capacity)[a]; (*_nodes)[m].sum += (*_capacity)[a]; int c = (*_nodes)[m].curr_arc; if (c != -1 && _arcs[c ^ 1].target == n) { _edges[c >> 1].capacity += (*_capacity)[a]; } else { _edges[index].capacity = (*_capacity)[a]; _arcs[index << 1].prev = -1; if ((*_nodes)[n].first_arc != -1) { _arcs[(*_nodes)[n].first_arc].prev = (index << 1); } _arcs[index << 1].next = (*_nodes)[n].first_arc; (*_nodes)[n].first_arc = (index << 1); _arcs[index << 1].target = m; (*_nodes)[m].curr_arc = (index << 1); _arcs[(index << 1) | 1].prev = -1; if ((*_nodes)[m].first_arc != -1) { _arcs[(*_nodes)[m].first_arc].prev = ((index << 1) | 1); } _arcs[(index << 1) | 1].next = (*_nodes)[m].first_arc; (*_nodes)[m].first_arc = ((index << 1) | 1); _arcs[(index << 1) | 1].target = n; ++index; } } } typename Graph::Node cut_node = INVALID; _min_cut = std::numeric_limits::max(); for (typename Graph::Node n = _first_node; n != INVALID; n = (*_nodes)[n].next) { if ((*_nodes)[n].sum < _min_cut) { cut_node = n; _min_cut = (*_nodes)[n].sum; } } (*_cut_map)[cut_node] = true; if (_min_cut == 0) { _first_node = INVALID; } } public: /// \brief Processes the next phase /// /// Processes the next phase in the algorithm. It must be called /// at most one less the number of the nodes in the graph. /// ///\return %True when the algorithm finished. bool processNextPhase() { if (_first_node == INVALID) return true; _heap->clear(); for (typename Graph::Node n = _first_node; n != INVALID; n = (*_nodes)[n].next) { (*_heap_cross_ref)[n] = Heap::PRE_HEAP; } std::vector order; order.reserve(_node_num); int sep = 0; Value alpha = 0; Value pmc = std::numeric_limits::max(); _heap->push(_first_node, static_cast(0)); while (!_heap->empty()) { typename Graph::Node n = _heap->top(); Value v = _heap->prio(); _heap->pop(); for (int a = (*_nodes)[n].first_arc; a != -1; a = _arcs[a].next) { switch (_heap->state(_arcs[a].target)) { case Heap::PRE_HEAP: { Value nv = _edges[a >> 1].capacity; _heap->push(_arcs[a].target, nv); _edges[a >> 1].cut = nv; } break; case Heap::IN_HEAP: { Value nv = _edges[a >> 1].capacity + (*_heap)[_arcs[a].target]; _heap->decrease(_arcs[a].target, nv); _edges[a >> 1].cut = nv; } break; case Heap::POST_HEAP: break; } } alpha += (*_nodes)[n].sum; alpha -= 2 * v; order.push_back(n); if (!_heap->empty()) { if (alpha < pmc) { pmc = alpha; sep = order.size(); } } } if (static_cast(order.size()) < _node_num) { _first_node = INVALID; for (typename Graph::NodeIt n(_graph); n != INVALID; ++n) { (*_cut_map)[n] = false; } for (int i = 0; i < static_cast(order.size()); ++i) { typename Graph::Node n = order[i]; while (n != INVALID) { (*_cut_map)[n] = true; n = (*_next_rep)[n]; } } _min_cut = 0; return true; } if (pmc < _min_cut) { for (typename Graph::NodeIt n(_graph); n != INVALID; ++n) { (*_cut_map)[n] = false; } for (int i = 0; i < sep; ++i) { typename Graph::Node n = order[i]; while (n != INVALID) { (*_cut_map)[n] = true; n = (*_next_rep)[n]; } } _min_cut = pmc; } for (typename Graph::Node n = _first_node; n != INVALID; n = (*_nodes)[n].next) { bool merged = false; for (int a = (*_nodes)[n].first_arc; a != -1; a = _arcs[a].next) { if (!(_edges[a >> 1].cut < pmc)) { if (!merged) { for (int b = (*_nodes)[n].first_arc; b != -1; b = _arcs[b].next) { (*_nodes)[_arcs[b].target].curr_arc = b; } merged = true; } typename Graph::Node m = _arcs[a].target; int nb = 0; for (int b = (*_nodes)[m].first_arc; b != -1; b = nb) { nb = _arcs[b].next; if ((b ^ a) == 1) continue; typename Graph::Node o = _arcs[b].target; int c = (*_nodes)[o].curr_arc; if (c != -1 && _arcs[c ^ 1].target == n) { _edges[c >> 1].capacity += _edges[b >> 1].capacity; (*_nodes)[n].sum += _edges[b >> 1].capacity; if (_edges[b >> 1].cut < _edges[c >> 1].cut) { _edges[b >> 1].cut = _edges[c >> 1].cut; } if (_arcs[b ^ 1].prev != -1) { _arcs[_arcs[b ^ 1].prev].next = _arcs[b ^ 1].next; } else { (*_nodes)[o].first_arc = _arcs[b ^ 1].next; } if (_arcs[b ^ 1].next != -1) { _arcs[_arcs[b ^ 1].next].prev = _arcs[b ^ 1].prev; } } else { if (_arcs[a].next != -1) { _arcs[_arcs[a].next].prev = b; } _arcs[b].next = _arcs[a].next; _arcs[b].prev = a; _arcs[a].next = b; _arcs[b ^ 1].target = n; (*_nodes)[n].sum += _edges[b >> 1].capacity; (*_nodes)[o].curr_arc = b; } } if (_arcs[a].prev != -1) { _arcs[_arcs[a].prev].next = _arcs[a].next; } else { (*_nodes)[n].first_arc = _arcs[a].next; } if (_arcs[a].next != -1) { _arcs[_arcs[a].next].prev = _arcs[a].prev; } (*_nodes)[n].sum -= _edges[a >> 1].capacity; (*_next_rep)[(*_nodes)[n].last_rep] = m; (*_nodes)[n].last_rep = (*_nodes)[m].last_rep; if ((*_nodes)[m].prev != INVALID) { (*_nodes)[(*_nodes)[m].prev].next = (*_nodes)[m].next; } else{ _first_node = (*_nodes)[m].next; } if ((*_nodes)[m].next != INVALID) { (*_nodes)[(*_nodes)[m].next].prev = (*_nodes)[m].prev; } --_node_num; } } } if (_node_num == 1) { _first_node = INVALID; return true; } return false; } /// \brief Executes the algorithm. /// /// Executes the algorithm. /// /// \pre init() must be called void start() { while (!processNextPhase()) {} } /// \brief Runs %NagamochiIbaraki algorithm. /// /// This method runs the %Min cut algorithm /// /// \note mc.run(s) is just a shortcut of the following code. ///\code /// mc.init(); /// mc.start(); ///\endcode void run() { init(); start(); } ///@} /// \name Query Functions /// /// The result of the %NagamochiIbaraki /// algorithm can be obtained using these functions.\n /// Before the use of these functions, either run() or start() /// must be called. ///@{ /// \brief Returns the min cut value. /// /// Returns the min cut value if the algorithm finished. /// After the first processNextPhase() it is a value of a /// valid cut in the graph. Value minCutValue() const { return _min_cut; } /// \brief Returns a min cut in a NodeMap. /// /// It sets the nodes of one of the two partitions to true and /// the other partition to false. /// \param cutMap A \ref concepts::WriteMap "writable" node map with /// \c bool (or convertible) value type. template Value minCutMap(CutMap& cutMap) const { for (typename Graph::NodeIt n(_graph); n != INVALID; ++n) { cutMap.set(n, (*_cut_map)[n]); } return minCutValue(); } ///@} }; } #endif