/* -*- mode: C++; indent-tabs-mode: nil; -*-
* This file is a part of LEMON, a generic C++ optimization library.
* Copyright (C) 2003-2011
* 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
#ifndef LEMON_MAX_MATCHING_H
#define LEMON_MAX_MATCHING_H
#include <lemon/unionfind.h>
#include <lemon/bin_heap.h>
///\brief Maximum matching algorithms in general graphs.
/// \brief Maximum cardinality matching in general graphs
/// This class implements Edmonds' alternating forest matching algorithm
/// for finding a maximum cardinality matching in a general undirected graph.
/// It can be started from an arbitrary initial matching
/// (the default is the empty one).
/// The dual solution of the problem is a map of the nodes to
/// \ref MaxMatching::Status "Status", having values \c EVEN (or \c D),
/// \c ODD (or \c A) and \c MATCHED (or \c C) defining the Gallai-Edmonds
/// decomposition of the graph. The nodes in \c EVEN/D induce a subgraph
/// with factor-critical components, the nodes in \c ODD/A form the
/// canonical barrier, and the nodes in \c MATCHED/C induce a graph having
/// a perfect matching. The number of the factor-critical components
/// minus the number of barrier nodes is a lower bound on the
/// unmatched nodes, and the matching is optimal if and only if this bound is
/// tight. This decomposition can be obtained using \ref status() or
/// \ref statusMap() after running the algorithm.
/// \tparam GR The undirected graph type the algorithm runs on.
/// The graph type of the algorithm
/// The type of the matching map
typedef typename Graph::template NodeMap<typename Graph::Arc>
///\brief Status constants for Gallai-Edmonds decomposition.
///These constants are used for indicating the Gallai-Edmonds
///decomposition of a graph. The nodes with status \c EVEN (or \c D)
///induce a subgraph with factor-critical components, the nodes with
///status \c ODD (or \c A) form the canonical barrier, and the nodes
///with status \c MATCHED (or \c C) induce a subgraph having a
EVEN = 1, ///< = 1. (\c D is an alias for \c EVEN.)
MATCHED = 0, ///< = 0. (\c C is an alias for \c MATCHED.)
ODD = -1, ///< = -1. (\c A is an alias for \c ODD.)
UNMATCHED = -2 ///< = -2.
/// The type of the status map
typedef typename Graph::template NodeMap<Status> StatusMap;
TEMPLATE_GRAPH_TYPEDEFS(Graph);
typedef UnionFindEnum<IntNodeMap> BlossomSet;
typedef ExtendFindEnum<IntNodeMap> TreeSet;
typedef RangeMap<Node> NodeIntMap;
typedef MatchingMap EarMap;
typedef std::vector<Node> NodeQueue;
IntNodeMap* _blossom_set_index;
BlossomSet* _blossom_set;
NodeIntMap* _blossom_rep;
IntNodeMap* _tree_set_index;
int _process, _postpone, _last;
void createStructures() {
_node_num = countNodes(_graph);
_matching = new MatchingMap(_graph);
_status = new StatusMap(_graph);
_ear = new EarMap(_graph);
_blossom_set_index = new IntNodeMap(_graph);
_blossom_set = new BlossomSet(*_blossom_set_index);
_blossom_rep = new NodeIntMap(_node_num);
_tree_set_index = new IntNodeMap(_graph);
_tree_set = new TreeSet(*_tree_set_index);
_node_queue.resize(_node_num);
void destroyStructures() {
delete _blossom_set_index;
void processDense(const Node& n) {
_process = _postpone = _last = 0;
_node_queue[_last++] = n;
while (_process != _last) {
Node u = _node_queue[_process++];
for (OutArcIt a(_graph, u); a != INVALID; ++a) {
Node v = _graph.target(a);
if ((*_status)[v] == MATCHED) {
} else if ((*_status)[v] == UNMATCHED) {
while (_postpone != _last) {
Node u = _node_queue[_postpone++];
for (OutArcIt a(_graph, u); a != INVALID ; ++a) {
Node v = _graph.target(a);
if ((*_status)[v] == EVEN) {
if (_blossom_set->find(u) != _blossom_set->find(v)) {
while (_process != _last) {
Node w = _node_queue[_process++];
for (OutArcIt b(_graph, w); b != INVALID; ++b) {
Node x = _graph.target(b);
if ((*_status)[x] == MATCHED) {
} else if ((*_status)[x] == UNMATCHED) {
void processSparse(const Node& n) {
_node_queue[_last++] = n;
while (_process != _last) {
Node u = _node_queue[_process++];
for (OutArcIt a(_graph, u); a != INVALID; ++a) {
Node v = _graph.target(a);
if ((*_status)[v] == EVEN) {
if (_blossom_set->find(u) != _blossom_set->find(v)) {
} else if ((*_status)[v] == MATCHED) {
} else if ((*_status)[v] == UNMATCHED) {
void shrinkOnEdge(const Edge& e) {
std::set<Node> left_set, right_set;
Node left = (*_blossom_rep)[_blossom_set->find(_graph.u(e))];
Node right = (*_blossom_rep)[_blossom_set->find(_graph.v(e))];
if ((*_matching)[left] == INVALID) break;
left = _graph.target((*_matching)[left]);
left = (*_blossom_rep)[_blossom_set->
find(_graph.target((*_ear)[left]))];
if (right_set.find(left) != right_set.end()) {
if ((*_matching)[right] == INVALID) break;
right = _graph.target((*_matching)[right]);
right = (*_blossom_rep)[_blossom_set->
find(_graph.target((*_ear)[right]))];
if (left_set.find(right) != left_set.end()) {
if ((*_matching)[left] == INVALID) {
while (left_set.find(nca) == left_set.end()) {
nca = _graph.target((*_matching)[nca]);
nca =(*_blossom_rep)[_blossom_set->
find(_graph.target((*_ear)[nca]))];
while (right_set.find(nca) == right_set.end()) {
nca = _graph.target((*_matching)[nca]);
nca = (*_blossom_rep)[_blossom_set->
find(_graph.target((*_ear)[nca]))];
Arc arc = _graph.direct(e, true);
Node base = (*_blossom_rep)[_blossom_set->find(node)];
n = _graph.target((*_matching)[n]);
(*_ear)[n] = _graph.oppositeArc(a);
node = _graph.target((*_matching)[base]);
_blossom_set->insert(node, _blossom_set->find(base));
_node_queue[_last++] = node;
arc = _graph.oppositeArc((*_ear)[node]);
node = _graph.target((*_ear)[node]);
base = (*_blossom_rep)[_blossom_set->find(node)];
_blossom_set->join(_graph.target(arc), base);
(*_blossom_rep)[_blossom_set->find(nca)] = nca;
Arc arc = _graph.direct(e, false);
Node base = (*_blossom_rep)[_blossom_set->find(node)];
n = _graph.target((*_matching)[n]);
(*_ear)[n] = _graph.oppositeArc(a);
node = _graph.target((*_matching)[base]);
_blossom_set->insert(node, _blossom_set->find(base));
_node_queue[_last++] = node;
arc = _graph.oppositeArc((*_ear)[node]);
node = _graph.target((*_ear)[node]);
base = (*_blossom_rep)[_blossom_set->find(node)];
_blossom_set->join(_graph.target(arc), base);
(*_blossom_rep)[_blossom_set->find(nca)] = nca;
void extendOnArc(const Arc& a) {
Node base = _graph.source(a);
Node odd = _graph.target(a);
(*_ear)[odd] = _graph.oppositeArc(a);
Node even = _graph.target((*_matching)[odd]);
(*_blossom_rep)[_blossom_set->insert(even)] = even;
int tree = _tree_set->find((*_blossom_rep)[_blossom_set->find(base)]);
_tree_set->insert(odd, tree);
_tree_set->insert(even, tree);
_node_queue[_last++] = even;
void augmentOnArc(const Arc& a) {
Node even = _graph.source(a);
Node odd = _graph.target(a);
int tree = _tree_set->find((*_blossom_rep)[_blossom_set->find(even)]);
(*_matching)[odd] = _graph.oppositeArc(a);
(*_status)[odd] = MATCHED;
Arc arc = (*_matching)[even];
odd = _graph.target(arc);
even = _graph.target(arc);
arc = (*_matching)[even];
(*_matching)[even] = _graph.oppositeArc((*_matching)[odd]);
for (typename TreeSet::ItemIt it(*_tree_set, tree);
if ((*_status)[it] == ODD) {
(*_status)[it] = MATCHED;
int blossom = _blossom_set->find(it);
for (typename BlossomSet::ItemIt jt(*_blossom_set, blossom);
(*_status)[jt] = MATCHED;
_blossom_set->eraseClass(blossom);
_tree_set->eraseClass(tree);
MaxMatching(const Graph& graph)
: _graph(graph), _matching(0), _status(0), _ear(0),
_blossom_set_index(0), _blossom_set(0), _blossom_rep(0),
_tree_set_index(0), _tree_set(0) {}
/// \name Execution Control
/// The simplest way to execute the algorithm is to use the
/// \c run() member function.\n
/// If you need better control on the execution, you have to call
/// one of the functions \ref init(), \ref greedyInit() or
/// \ref matchingInit() first, then you can start the algorithm with
/// \ref startSparse() or \ref startDense().
/// \brief Set the initial matching to the empty matching.
/// This function sets the initial matching to the empty matching.
for(NodeIt n(_graph); n != INVALID; ++n) {
(*_matching)[n] = INVALID;
(*_status)[n] = UNMATCHED;
/// \brief Find an initial matching in a greedy way.
/// This function finds an initial matching in a greedy way.
for (NodeIt n(_graph); n != INVALID; ++n) {
(*_matching)[n] = INVALID;
(*_status)[n] = UNMATCHED;
for (NodeIt n(_graph); n != INVALID; ++n) {
if ((*_matching)[n] == INVALID) {
for (OutArcIt a(_graph, n); a != INVALID ; ++a) {
Node v = _graph.target(a);
if ((*_matching)[v] == INVALID && v != n) {
(*_matching)[v] = _graph.oppositeArc(a);
/// \brief Initialize the matching from a map.
/// This function initializes the matching from a \c bool valued edge
/// map. This map should have the property that there are no two incident
/// edges with \c true value, i.e. it really contains a matching.
/// \return \c true if the map contains a matching.
template <typename MatchingMap>
bool matchingInit(const MatchingMap& matching) {
for (NodeIt n(_graph); n != INVALID; ++n) {
(*_matching)[n] = INVALID;
(*_status)[n] = UNMATCHED;
for(EdgeIt e(_graph); e!=INVALID; ++e) {
if ((*_matching)[u] != INVALID) return false;
(*_matching)[u] = _graph.direct(e, true);
if ((*_matching)[v] != INVALID) return false;
(*_matching)[v] = _graph.direct(e, false);
/// \brief Start Edmonds' algorithm
/// This function runs the original Edmonds' algorithm.
/// \pre \ref init(), \ref greedyInit() or \ref matchingInit() must be
/// called before using this function.
for(NodeIt n(_graph); n != INVALID; ++n) {
if ((*_status)[n] == UNMATCHED) {
(*_blossom_rep)[_blossom_set->insert(n)] = n;
/// \brief Start Edmonds' algorithm with a heuristic improvement
/// This function runs Edmonds' algorithm with a heuristic of postponing
/// shrinks, therefore resulting in a faster algorithm for dense graphs.
/// \pre \ref init(), \ref greedyInit() or \ref matchingInit() must be
/// called before using this function.
for(NodeIt n(_graph); n != INVALID; ++n) {
if ((*_status)[n] == UNMATCHED) {
(*_blossom_rep)[_blossom_set->insert(n)] = n;
/// \brief Run Edmonds' algorithm
/// This function runs Edmonds' algorithm. An additional heuristic of
/// postponing shrinks is used for relatively dense graphs
/// (for which <tt>m>=2*n</tt> holds).
if (countEdges(_graph) < 2 * countNodes(_graph)) {
/// \name Primal Solution
/// Functions to get the primal solution, i.e. the maximum matching.
/// \brief Return the size (cardinality) of the matching.
/// This function returns the size (cardinality) of the current matching.
/// After run() it returns the size of the maximum matching in the graph.
int matchingSize() const {
for (NodeIt n(_graph); n != INVALID; ++n) {
if ((*_matching)[n] != INVALID) {
/// \brief Return \c true if the given edge is in the matching.
/// This function returns \c true if the given edge is in the current
bool matching(const Edge& edge) const {
return edge == (*_matching)[_graph.u(edge)];
/// \brief Return the matching arc (or edge) incident to the given node.
/// This function returns the matching arc (or edge) incident to the
/// given node in the current matching or \c INVALID if the node is
/// not covered by the matching.
Arc matching(const Node& n) const {
/// \brief Return a const reference to the matching map.
/// This function returns a const reference to a node map that stores
/// the matching arc (or edge) incident to each node.
const MatchingMap& matchingMap() const {
/// \brief Return the mate of the given node.
/// This function returns the mate of the given node in the current
/// matching or \c INVALID if the node is not covered by the matching.
Node mate(const Node& n) const {
return (*_matching)[n] != INVALID ?
_graph.target((*_matching)[n]) : INVALID;
/// Functions to get the dual solution, i.e. the Gallai-Edmonds
/// \brief Return the status of the given node in the Edmonds-Gallai
/// This function returns the \ref Status "status" of the given node
/// in the Edmonds-Gallai decomposition.
Status status(const Node& n) const {
/// \brief Return a const reference to the status map, which stores
/// the Edmonds-Gallai decomposition.
/// This function returns a const reference to a node map that stores the
/// \ref Status "status" of each node in the Edmonds-Gallai decomposition.
const StatusMap& statusMap() const {
/// \brief Return \c true if the given node is in the barrier.
/// This function returns \c true if the given node is in the barrier.
bool barrier(const Node& n) const {
return (*_status)[n] == ODD;
/// \brief Weighted matching in general graphs
/// This class provides an efficient implementation of Edmond's
/// maximum weighted matching algorithm. The implementation is based
/// on extensive use of priority queues and provides
/// \f$O(nm\log n)\f$ time complexity.
/// The maximum weighted matching problem is to find a subset of the
/// edges in an undirected graph with maximum overall weight for which
/// each node has at most one incident edge.
/// It can be formulated with the following linear program.
/// \f[ \sum_{e \in \delta(u)}x_e \le 1 \quad \forall u\in V\f]
/** \f[ \sum_{e \in \gamma(B)}x_e \le \frac{\vert B \vert - 1}{2}
\quad \forall B\in\mathcal{O}\f] */
/// \f[x_e \ge 0\quad \forall e\in E\f]
/// \f[\max \sum_{e\in E}x_ew_e\f]
/// where \f$\delta(X)\f$ is the set of edges incident to a node in
/// \f$X\f$, \f$\gamma(X)\f$ is the set of edges with both ends in
/// \f$X\f$ and \f$\mathcal{O}\f$ is the set of odd cardinality
/// subsets of the nodes.
/// The algorithm calculates an optimal matching and a proof of the
/// optimality. The solution of the dual problem can be used to check
/// the result of the algorithm. The dual linear problem is the
/** \f[ y_u + y_v + \sum_{B \in \mathcal{O}, uv \in \gamma(B)}
z_B \ge w_{uv} \quad \forall uv\in E\f] */
/// \f[y_u \ge 0 \quad \forall u \in V\f]
/// \f[z_B \ge 0 \quad \forall B \in \mathcal{O}\f]
/** \f[\min \sum_{u \in V}y_u + \sum_{B \in \mathcal{O}}
\frac{\vert B \vert - 1}{2}z_B\f] */
/// The algorithm can be executed with the run() function.
/// After it the matching (the primal solution) and the dual solution
/// can be obtained using the query functions and the
/// \ref MaxWeightedMatching::BlossomIt "BlossomIt" nested class,
/// which is able to iterate on the nodes of a blossom.
/// If the value type is integer, then the dual solution is multiplied
/// by \ref MaxWeightedMatching::dualScale "4".
/// \tparam GR The undirected graph type the algorithm runs on.
/// \tparam WM The type edge weight map. The default type is
/// \ref concepts::Graph::EdgeMap "GR::EdgeMap<int>".
template <typename GR, typename WM>
typename WM = typename GR::template EdgeMap<int> >
class MaxWeightedMatching {
/// The graph type of the algorithm
/// The type of the edge weight map
/// The value type of the edge weights
typedef typename WeightMap::Value Value;
/// The type of the matching map
typedef typename Graph::template NodeMap<typename Graph::Arc>
/// \brief Scaling factor for dual solution
/// Scaling factor for dual solution. It is equal to 4 or 1
/// according to the value type.
static const int dualScale =
std::numeric_limits<Value>::is_integer ? 4 : 1;
TEMPLATE_GRAPH_TYPEDEFS(Graph);
typedef typename Graph::template NodeMap<Value> NodePotential;
typedef std::vector<Node> BlossomNodeList;
BlossomVariable(int _begin, int _end, Value _value)
: begin(_begin), end(_end), value(_value) {}
typedef std::vector<BlossomVariable> BlossomPotential;
const WeightMap& _weight;
NodePotential* _node_potential;
BlossomPotential _blossom_potential;
BlossomNodeList _blossom_node_list;
typedef RangeMap<int> IntIntMap;
EVEN = -1, MATCHED = 0, ODD = 1, UNMATCHED = -2
typedef HeapUnionFind<Value, IntNodeMap> BlossomSet;
IntNodeMap *_blossom_index;
BlossomSet *_blossom_set;
RangeMap<BlossomData>* _blossom_data;
IntArcMap *_node_heap_index;
NodeData(IntArcMap& node_heap_index)
: heap(node_heap_index) {}
BinHeap<Value, IntArcMap> heap;
std::map<int, Arc> heap_index;
RangeMap<NodeData>* _node_data;
typedef ExtendFindEnum<IntIntMap> TreeSet;
IntIntMap *_tree_set_index;
IntNodeMap *_delta1_index;
BinHeap<Value, IntNodeMap> *_delta1;
IntIntMap *_delta2_index;
BinHeap<Value, IntIntMap> *_delta2;
IntEdgeMap *_delta3_index;
BinHeap<Value, IntEdgeMap> *_delta3;
IntIntMap *_delta4_index;
BinHeap<Value, IntIntMap> *_delta4;
void createStructures() {
_node_num = countNodes(_graph);
_blossom_num = _node_num * 3 / 2;
_matching = new MatchingMap(_graph);
_node_potential = new NodePotential(_graph);
_blossom_index = new IntNodeMap(_graph);
_blossom_set = new BlossomSet(*_blossom_index);
_blossom_data = new RangeMap<BlossomData>(_blossom_num);
} else if (_blossom_data->size() != _blossom_num) {
_blossom_data = new RangeMap<BlossomData>(_blossom_num);
_node_index = new IntNodeMap(_graph);
_node_heap_index = new IntArcMap(_graph);
_node_data = new RangeMap<NodeData>(_node_num,
NodeData(*_node_heap_index));
_node_data = new RangeMap<NodeData>(_node_num,
NodeData(*_node_heap_index));
_tree_set_index = new IntIntMap(_blossom_num);
_tree_set = new TreeSet(*_tree_set_index);
_tree_set_index->resize(_blossom_num);
_delta1_index = new IntNodeMap(_graph);
_delta1 = new BinHeap<Value, IntNodeMap>(*_delta1_index);
_delta2_index = new IntIntMap(_blossom_num);
_delta2 = new BinHeap<Value, IntIntMap>(*_delta2_index);
_delta2_index->resize(_blossom_num);
_delta3_index = new IntEdgeMap(_graph);
_delta3 = new BinHeap<Value, IntEdgeMap>(*_delta3_index);
_delta4_index = new IntIntMap(_blossom_num);
_delta4 = new BinHeap<Value, IntIntMap>(*_delta4_index);
_delta4_index->resize(_blossom_num);
void destroyStructures() {
_node_num = countNodes(_graph);
_blossom_num = _node_num * 3 / 2;
void matchedToEven(int blossom, int tree) {
if (_delta2->state(blossom) == _delta2->IN_HEAP) {
if (!_blossom_set->trivial(blossom)) {
(*_blossom_data)[blossom].pot -=
2 * (_delta_sum - (*_blossom_data)[blossom].offset);
for (typename BlossomSet::ItemIt n(*_blossom_set, blossom);
_blossom_set->increase(n, std::numeric_limits<Value>::max());
int ni = (*_node_index)[n];
(*_node_data)[ni].heap.clear();
(*_node_data)[ni].heap_index.clear();
(*_node_data)[ni].pot += _delta_sum - (*_blossom_data)[blossom].offset;
_delta1->push(n, (*_node_data)[ni].pot);
for (InArcIt e(_graph, n); e != INVALID; ++e) {
Node v = _graph.source(e);
int vb = _blossom_set->find(v);
int vi = (*_node_index)[v];
Value rw = (*_node_data)[ni].pot + (*_node_data)[vi].pot -
if ((*_blossom_data)[vb].status == EVEN) {
if (_delta3->state(e) != _delta3->IN_HEAP && blossom != vb) {
_delta3->push(e, rw / 2);
} else if ((*_blossom_data)[vb].status == UNMATCHED) {
if (_delta3->state(e) != _delta3->IN_HEAP) {
typename std::map<int, Arc>::iterator it =
(*_node_data)[vi].heap_index.find(tree);
if (it != (*_node_data)[vi].heap_index.end()) {
if ((*_node_data)[vi].heap[it->second] > rw) {
(*_node_data)[vi].heap.replace(it->second, e);
(*_node_data)[vi].heap.decrease(e, rw);
(*_node_data)[vi].heap.push(e, rw);
(*_node_data)[vi].heap_index.insert(std::make_pair(tree, e));
if ((*_blossom_set)[v] > (*_node_data)[vi].heap.prio()) {
_blossom_set->decrease(v, (*_node_data)[vi].heap.prio());
if ((*_blossom_data)[vb].status == MATCHED) {
if (_delta2->state(vb) != _delta2->IN_HEAP) {
_delta2->push(vb, _blossom_set->classPrio(vb) -
(*_blossom_data)[vb].offset);
} else if ((*_delta2)[vb] > _blossom_set->classPrio(vb) -
(*_blossom_data)[vb].offset){
_delta2->decrease(vb, _blossom_set->classPrio(vb) -
(*_blossom_data)[vb].offset);
(*_blossom_data)[blossom].offset = 0;
void matchedToOdd(int blossom) {
if (_delta2->state(blossom) == _delta2->IN_HEAP) {
(*_blossom_data)[blossom].offset += _delta_sum;
if (!_blossom_set->trivial(blossom)) {
_delta4->push(blossom, (*_blossom_data)[blossom].pot / 2 +
(*_blossom_data)[blossom].offset);
void evenToMatched(int blossom, int tree) {
if (!_blossom_set->trivial(blossom)) {
(*_blossom_data)[blossom].pot += 2 * _delta_sum;
for (typename BlossomSet::ItemIt n(*_blossom_set, blossom);
int ni = (*_node_index)[n];
(*_node_data)[ni].pot -= _delta_sum;
for (InArcIt e(_graph, n); e != INVALID; ++e) {
Node v = _graph.source(e);
int vb = _blossom_set->find(v);
int vi = (*_node_index)[v];
Value rw = (*_node_data)[ni].pot + (*_node_data)[vi].pot -
if (_delta3->state(e) == _delta3->IN_HEAP) {
} else if ((*_blossom_data)[vb].status == EVEN) {
if (_delta3->state(e) == _delta3->IN_HEAP) {
int vt = _tree_set->find(vb);
Arc r = _graph.oppositeArc(e);
typename std::map<int, Arc>::iterator it =
(*_node_data)[ni].heap_index.find(vt);
if (it != (*_node_data)[ni].heap_index.end()) {
if ((*_node_data)[ni].heap[it->second] > rw) {
(*_node_data)[ni].heap.replace(it->second, r);
(*_node_data)[ni].heap.decrease(r, rw);
(*_node_data)[ni].heap.push(r, rw);
(*_node_data)[ni].heap_index.insert(std::make_pair(vt, r));
if ((*_blossom_set)[n] > (*_node_data)[ni].heap.prio()) {
_blossom_set->decrease(n, (*_node_data)[ni].heap.prio());
if (_delta2->state(blossom) != _delta2->IN_HEAP) {
_delta2->push(blossom, _blossom_set->classPrio(blossom) -
(*_blossom_data)[blossom].offset);
} else if ((*_delta2)[blossom] >
_blossom_set->classPrio(blossom) -
(*_blossom_data)[blossom].offset){
_delta2->decrease(blossom, _blossom_set->classPrio(blossom) -
(*_blossom_data)[blossom].offset);
} else if ((*_blossom_data)[vb].status == UNMATCHED) {
if (_delta3->state(e) == _delta3->IN_HEAP) {
typename std::map<int, Arc>::iterator it =
(*_node_data)[vi].heap_index.find(tree);
if (it != (*_node_data)[vi].heap_index.end()) {
(*_node_data)[vi].heap.erase(it->second);
(*_node_data)[vi].heap_index.erase(it);
if ((*_node_data)[vi].heap.empty()) {
_blossom_set->increase(v, std::numeric_limits<Value>::max());
} else if ((*_blossom_set)[v] < (*_node_data)[vi].heap.prio()) {
_blossom_set->increase(v, (*_node_data)[vi].heap.prio());
if ((*_blossom_data)[vb].status == MATCHED) {
if (_blossom_set->classPrio(vb) ==
std::numeric_limits<Value>::max()) {
} else if ((*_delta2)[vb] < _blossom_set->classPrio(vb) -
(*_blossom_data)[vb].offset) {
_delta2->increase(vb, _blossom_set->classPrio(vb) -
(*_blossom_data)[vb].offset);
void oddToMatched(int blossom) {
(*_blossom_data)[blossom].offset -= _delta_sum;
if (_blossom_set->classPrio(blossom) !=
std::numeric_limits<Value>::max()) {
_delta2->push(blossom, _blossom_set->classPrio(blossom) -
(*_blossom_data)[blossom].offset);
if (!_blossom_set->trivial(blossom)) {
void oddToEven(int blossom, int tree) {
if (!_blossom_set->trivial(blossom)) {
(*_blossom_data)[blossom].pot -=
2 * (2 * _delta_sum - (*_blossom_data)[blossom].offset);
for (typename BlossomSet::ItemIt n(*_blossom_set, blossom);
int ni = (*_node_index)[n];
_blossom_set->increase(n, std::numeric_limits<Value>::max());
(*_node_data)[ni].heap.clear();
(*_node_data)[ni].heap_index.clear();
2 * _delta_sum - (*_blossom_data)[blossom].offset;
_delta1->push(n, (*_node_data)[ni].pot);
for (InArcIt e(_graph, n); e != INVALID; ++e) {
Node v = _graph.source(e);
int vb = _blossom_set->find(v);
int vi = (*_node_index)[v];
Value rw = (*_node_data)[ni].pot + (*_node_data)[vi].pot -
if ((*_blossom_data)[vb].status == EVEN) {
if (_delta3->state(e) != _delta3->IN_HEAP && blossom != vb) {
_delta3->push(e, rw / 2);
} else if ((*_blossom_data)[vb].status == UNMATCHED) {
if (_delta3->state(e) != _delta3->IN_HEAP) {
typename std::map<int, Arc>::iterator it =
(*_node_data)[vi].heap_index.find(tree);
if (it != (*_node_data)[vi].heap_index.end()) {
if ((*_node_data)[vi].heap[it->second] > rw) {
(*_node_data)[vi].heap.replace(it->second, e);
(*_node_data)[vi].heap.decrease(e, rw);
(*_node_data)[vi].heap.push(e, rw);
(*_node_data)[vi].heap_index.insert(std::make_pair(tree, e));
if ((*_blossom_set)[v] > (*_node_data)[vi].heap.prio()) {
_blossom_set->decrease(v, (*_node_data)[vi].heap.prio());
if ((*_blossom_data)[vb].status == MATCHED) {
if (_delta2->state(vb) != _delta2->IN_HEAP) {
_delta2->push(vb, _blossom_set->classPrio(vb) -
(*_blossom_data)[vb].offset);
} else if ((*_delta2)[vb] > _blossom_set->classPrio(vb) -
(*_blossom_data)[vb].offset) {
_delta2->decrease(vb, _blossom_set->classPrio(vb) -
(*_blossom_data)[vb].offset);
(*_blossom_data)[blossom].offset = 0;
void matchedToUnmatched(int blossom) {
if (_delta2->state(blossom) == _delta2->IN_HEAP) {
for (typename BlossomSet::ItemIt n(*_blossom_set, blossom);
int ni = (*_node_index)[n];
_blossom_set->increase(n, std::numeric_limits<Value>::max());
(*_node_data)[ni].heap.clear();
(*_node_data)[ni].heap_index.clear();
for (OutArcIt e(_graph, n); e != INVALID; ++e) {
Node v = _graph.target(e);
int vb = _blossom_set->find(v);
int vi = (*_node_index)[v];
Value rw = (*_node_data)[ni].pot + (*_node_data)[vi].pot -
if ((*_blossom_data)[vb].status == EVEN) {
if (_delta3->state(e) != _delta3->IN_HEAP) {
void unmatchedToMatched(int blossom) {
for (typename BlossomSet::ItemIt n(*_blossom_set, blossom);
int ni = (*_node_index)[n];
for (InArcIt e(_graph, n); e != INVALID; ++e) {
Node v = _graph.source(e);
int vb = _blossom_set->find(v);
int vi = (*_node_index)[v];
Value rw = (*_node_data)[ni].pot + (*_node_data)[vi].pot -
if (_delta3->state(e) == _delta3->IN_HEAP) {
} else if ((*_blossom_data)[vb].status == EVEN) {
if (_delta3->state(e) == _delta3->IN_HEAP) {
int vt = _tree_set->find(vb);
Arc r = _graph.oppositeArc(e);
typename std::map<int, Arc>::iterator it =
(*_node_data)[ni].heap_index.find(vt);
if (it != (*_node_data)[ni].heap_index.end()) {
if ((*_node_data)[ni].heap[it->second] > rw) {
(*_node_data)[ni].heap.replace(it->second, r);
(*_node_data)[ni].heap.decrease(r, rw);
(*_node_data)[ni].heap.push(r, rw);
(*_node_data)[ni].heap_index.insert(std::make_pair(vt, r));
if ((*_blossom_set)[n] > (*_node_data)[ni].heap.prio()) {
_blossom_set->decrease(n, (*_node_data)[ni].heap.prio());
if (_delta2->state(blossom) != _delta2->IN_HEAP) {
_delta2->push(blossom, _blossom_set->classPrio(blossom) -
(*_blossom_data)[blossom].offset);
} else if ((*_delta2)[blossom] > _blossom_set->classPrio(blossom)-
(*_blossom_data)[blossom].offset){
_delta2->decrease(blossom, _blossom_set->classPrio(blossom) -
(*_blossom_data)[blossom].offset);
} else if ((*_blossom_data)[vb].status == UNMATCHED) {
if (_delta3->state(e) == _delta3->IN_HEAP) {
void alternatePath(int even, int tree) {
evenToMatched(even, tree);
(*_blossom_data)[even].status = MATCHED;
while ((*_blossom_data)[even].pred != INVALID) {
odd = _blossom_set->find(_graph.target((*_blossom_data)[even].pred));
(*_blossom_data)[odd].status = MATCHED;
(*_blossom_data)[odd].next = (*_blossom_data)[odd].pred;
even = _blossom_set->find(_graph.target((*_blossom_data)[odd].pred));
(*_blossom_data)[even].status = MATCHED;
evenToMatched(even, tree);
(*_blossom_data)[even].next =
_graph.oppositeArc((*_blossom_data)[odd].pred);
void destroyTree(int tree) {
for (TreeSet::ItemIt b(*_tree_set, tree); b != INVALID; ++b) {
if ((*_blossom_data)[b].status == EVEN) {
(*_blossom_data)[b].status = MATCHED;
} else if ((*_blossom_data)[b].status == ODD) {
(*_blossom_data)[b].status = MATCHED;
_tree_set->eraseClass(tree);
void unmatchNode(const Node& node) {
int blossom = _blossom_set->find(node);
int tree = _tree_set->find(blossom);
alternatePath(blossom, tree);
(*_blossom_data)[blossom].status = UNMATCHED;
(*_blossom_data)[blossom].base = node;
matchedToUnmatched(blossom);
void augmentOnEdge(const Edge& edge) {
int left = _blossom_set->find(_graph.u(edge));
int right = _blossom_set->find(_graph.v(edge));
if ((*_blossom_data)[left].status == EVEN) {
int left_tree = _tree_set->find(left);
alternatePath(left, left_tree);
(*_blossom_data)[left].status = MATCHED;
unmatchedToMatched(left);
if ((*_blossom_data)[right].status == EVEN) {
int right_tree = _tree_set->find(right);
alternatePath(right, right_tree);
(*_blossom_data)[right].status = MATCHED;
unmatchedToMatched(right);
(*_blossom_data)[left].next = _graph.direct(edge, true);
(*_blossom_data)[right].next = _graph.direct(edge, false);
void extendOnArc(const Arc& arc) {
int base = _blossom_set->find(_graph.target(arc));
int tree = _tree_set->find(base);
int odd = _blossom_set->find(_graph.source(arc));
_tree_set->insert(odd, tree);
(*_blossom_data)[odd].status = ODD;
(*_blossom_data)[odd].pred = arc;
int even = _blossom_set->find(_graph.target((*_blossom_data)[odd].next));
(*_blossom_data)[even].pred = (*_blossom_data)[even].next;
_tree_set->insert(even, tree);
(*_blossom_data)[even].status = EVEN;
matchedToEven(even, tree);
void shrinkOnEdge(const Edge& edge, int tree) {
std::vector<int> left_path, right_path;
std::set<int> left_set, right_set;
int left = _blossom_set->find(_graph.u(edge));
left_path.push_back(left);
int right = _blossom_set->find(_graph.v(edge));
right_path.push_back(right);
if ((*_blossom_data)[left].pred == INVALID) break;
_blossom_set->find(_graph.target((*_blossom_data)[left].pred));
left_path.push_back(left);
_blossom_set->find(_graph.target((*_blossom_data)[left].pred));
left_path.push_back(left);
if (right_set.find(left) != right_set.end()) {
if ((*_blossom_data)[right].pred == INVALID) break;
_blossom_set->find(_graph.target((*_blossom_data)[right].pred));
right_path.push_back(right);
_blossom_set->find(_graph.target((*_blossom_data)[right].pred));
right_path.push_back(right);
if (left_set.find(right) != left_set.end()) {
if ((*_blossom_data)[left].pred == INVALID) {
while (left_set.find(nca) == left_set.end()) {
_blossom_set->find(_graph.target((*_blossom_data)[nca].pred));
right_path.push_back(nca);
_blossom_set->find(_graph.target((*_blossom_data)[nca].pred));
right_path.push_back(nca);
while (right_set.find(nca) == right_set.end()) {
_blossom_set->find(_graph.target((*_blossom_data)[nca].pred));
left_path.push_back(nca);
_blossom_set->find(_graph.target((*_blossom_data)[nca].pred));
left_path.push_back(nca);
std::vector<int> subblossoms;
prev = _graph.direct(edge, true);
for (int i = 0; left_path[i] != nca; i += 2) {
subblossoms.push_back(left_path[i]);
(*_blossom_data)[left_path[i]].next = prev;
_tree_set->erase(left_path[i]);
subblossoms.push_back(left_path[i + 1]);
(*_blossom_data)[left_path[i + 1]].status = EVEN;
oddToEven(left_path[i + 1], tree);
_tree_set->erase(left_path[i + 1]);
prev = _graph.oppositeArc((*_blossom_data)[left_path[i + 1]].pred);
while (right_path[k] != nca) ++k;
subblossoms.push_back(nca);
(*_blossom_data)[nca].next = prev;
for (int i = k - 2; i >= 0; i -= 2) {
subblossoms.push_back(right_path[i + 1]);
(*_blossom_data)[right_path[i + 1]].status = EVEN;
oddToEven(right_path[i + 1], tree);
_tree_set->erase(right_path[i + 1]);
(*_blossom_data)[right_path[i + 1]].next =
(*_blossom_data)[right_path[i + 1]].pred;
subblossoms.push_back(right_path[i]);
_tree_set->erase(right_path[i]);
_blossom_set->join(subblossoms.begin(), subblossoms.end());
for (int i = 0; i < int(subblossoms.size()); ++i) {
if (!_blossom_set->trivial(subblossoms[i])) {
(*_blossom_data)[subblossoms[i]].pot += 2 * _delta_sum;
(*_blossom_data)[subblossoms[i]].status = MATCHED;
(*_blossom_data)[surface].pot = -2 * _delta_sum;
(*_blossom_data)[surface].offset = 0;
(*_blossom_data)[surface].status = EVEN;
(*_blossom_data)[surface].pred = (*_blossom_data)[nca].pred;
(*_blossom_data)[surface].next = (*_blossom_data)[nca].pred;
_tree_set->insert(surface, tree);
void splitBlossom(int blossom) {
Arc next = (*_blossom_data)[blossom].next;
Arc pred = (*_blossom_data)[blossom].pred;
int tree = _tree_set->find(blossom);
(*_blossom_data)[blossom].status = MATCHED;
if (_delta2->state(blossom) == _delta2->IN_HEAP) {
std::vector<int> subblossoms;
_blossom_set->split(blossom, std::back_inserter(subblossoms));
Value offset = (*_blossom_data)[blossom].offset;
int b = _blossom_set->find(_graph.source(pred));
int d = _blossom_set->find(_graph.source(next));
for (int i = 0; i < int(subblossoms.size()); ++i) {
if (subblossoms[i] == b) ib = i;
if (subblossoms[i] == d) id = i;
(*_blossom_data)[subblossoms[i]].offset = offset;
if (!_blossom_set->trivial(subblossoms[i])) {
(*_blossom_data)[subblossoms[i]].pot -= 2 * offset;
if (_blossom_set->classPrio(subblossoms[i]) !=
std::numeric_limits<Value>::max()) {
_delta2->push(subblossoms[i],
_blossom_set->classPrio(subblossoms[i]) -
(*_blossom_data)[subblossoms[i]].offset);
if (id > ib ? ((id - ib) % 2 == 0) : ((ib - id) % 2 == 1)) {
for (int i = (id + 1) % subblossoms.size();
i != ib; i = (i + 2) % subblossoms.size()) {
int tb = subblossoms[(i + 1) % subblossoms.size()];
(*_blossom_data)[sb].next =
_graph.oppositeArc((*_blossom_data)[tb].next);
for (int i = ib; i != id; i = (i + 2) % subblossoms.size()) {
int tb = subblossoms[(i + 1) % subblossoms.size()];
int ub = subblossoms[(i + 2) % subblossoms.size()];
(*_blossom_data)[sb].status = ODD;
_tree_set->insert(sb, tree);
(*_blossom_data)[sb].pred = pred;
(*_blossom_data)[sb].next =
_graph.oppositeArc((*_blossom_data)[tb].next);
pred = (*_blossom_data)[ub].next;
(*_blossom_data)[tb].status = EVEN;
_tree_set->insert(tb, tree);
(*_blossom_data)[tb].pred = (*_blossom_data)[tb].next;
(*_blossom_data)[subblossoms[id]].status = ODD;
matchedToOdd(subblossoms[id]);
_tree_set->insert(subblossoms[id], tree);
(*_blossom_data)[subblossoms[id]].next = next;
(*_blossom_data)[subblossoms[id]].pred = pred;
for (int i = (ib + 1) % subblossoms.size();
i != id; i = (i + 2) % subblossoms.size()) {
int tb = subblossoms[(i + 1) % subblossoms.size()];
(*_blossom_data)[sb].next =
_graph.oppositeArc((*_blossom_data)[tb].next);
for (int i = id; i != ib; i = (i + 2) % subblossoms.size()) {
int tb = subblossoms[(i + 1) % subblossoms.size()];
int ub = subblossoms[(i + 2) % subblossoms.size()];
(*_blossom_data)[sb].status = ODD;
_tree_set->insert(sb, tree);
(*_blossom_data)[sb].next = next;
(*_blossom_data)[sb].pred =
_graph.oppositeArc((*_blossom_data)[tb].next);
(*_blossom_data)[tb].status = EVEN;
_tree_set->insert(tb, tree);
(*_blossom_data)[tb].pred =
(*_blossom_data)[tb].next =
_graph.oppositeArc((*_blossom_data)[ub].next);
next = (*_blossom_data)[ub].next;
(*_blossom_data)[subblossoms[ib]].status = ODD;
matchedToOdd(subblossoms[ib]);
_tree_set->insert(subblossoms[ib], tree);
(*_blossom_data)[subblossoms[ib]].next = next;
(*_blossom_data)[subblossoms[ib]].pred = pred;
_tree_set->erase(blossom);
void extractBlossom(int blossom, const Node& base, const Arc& matching) {
if (_blossom_set->trivial(blossom)) {
int bi = (*_node_index)[base];
Value pot = (*_node_data)[bi].pot;
(*_matching)[base] = matching;
_blossom_node_list.push_back(base);
(*_node_potential)[base] = pot;
Value pot = (*_blossom_data)[blossom].pot;
int bn = _blossom_node_list.size();
std::vector<int> subblossoms;
_blossom_set->split(blossom, std::back_inserter(subblossoms));
int b = _blossom_set->find(base);
for (int i = 0; i < int(subblossoms.size()); ++i) {
if (subblossoms[i] == b) { ib = i; break; }
for (int i = 1; i < int(subblossoms.size()); i += 2) {
int sb = subblossoms[(ib + i) % subblossoms.size()];
int tb = subblossoms[(ib + i + 1) % subblossoms.size()];
Arc m = (*_blossom_data)[tb].next;
extractBlossom(sb, _graph.target(m), _graph.oppositeArc(m));
extractBlossom(tb, _graph.source(m), m);
extractBlossom(subblossoms[ib], base, matching);
int en = _blossom_node_list.size();
_blossom_potential.push_back(BlossomVariable(bn, en, pot));
std::vector<int> blossoms;
for (typename BlossomSet::ClassIt c(*_blossom_set); c != INVALID; ++c) {
for (int i = 0; i < int(blossoms.size()); ++i) {
if ((*_blossom_data)[blossoms[i]].status == MATCHED) {
Value offset = (*_blossom_data)[blossoms[i]].offset;
(*_blossom_data)[blossoms[i]].pot += 2 * offset;
for (typename BlossomSet::ItemIt n(*_blossom_set, blossoms[i]);
(*_node_data)[(*_node_index)[n]].pot -= offset;
Arc matching = (*_blossom_data)[blossoms[i]].next;
Node base = _graph.source(matching);
extractBlossom(blossoms[i], base, matching);
Node base = (*_blossom_data)[blossoms[i]].base;
extractBlossom(blossoms[i], base, INVALID);
MaxWeightedMatching(const Graph& graph, const WeightMap& weight)
: _graph(graph), _weight(weight), _matching(0),
_node_potential(0), _blossom_potential(), _blossom_node_list(),
_node_num(0), _blossom_num(0),
_blossom_index(0), _blossom_set(0), _blossom_data(0),
_node_index(0), _node_heap_index(0), _node_data(0),
_tree_set_index(0), _tree_set(0),
_delta1_index(0), _delta1(0),
_delta2_index(0), _delta2(0),
_delta3_index(0), _delta3(0),
_delta4_index(0), _delta4(0),
/// \name Execution Control
/// The simplest way to execute the algorithm is to use the
/// \ref run() member function.
/// \brief Initialize the algorithm
/// This function initializes the algorithm.
_blossom_node_list.clear();
_blossom_potential.clear();
for (ArcIt e(_graph); e != INVALID; ++e) {
(*_node_heap_index)[e] = BinHeap<Value, IntArcMap>::PRE_HEAP;
for (NodeIt n(_graph); n != INVALID; ++n) {
(*_delta1_index)[n] = _delta1->PRE_HEAP;
for (EdgeIt e(_graph); e != INVALID; ++e) {
(*_delta3_index)[e] = _delta3->PRE_HEAP;
for (int i = 0; i < _blossom_num; ++i) {
(*_delta2_index)[i] = _delta2->PRE_HEAP;
(*_delta4_index)[i] = _delta4->PRE_HEAP;
for (NodeIt n(_graph); n != INVALID; ++n) {
for (OutArcIt e(_graph, n); e != INVALID; ++e) {
if (_graph.target(e) == n) continue;
if ((dualScale * _weight[e]) / 2 > max) {
max = (dualScale * _weight[e]) / 2;
(*_node_index)[n] = index;
(*_node_data)[index].heap_index.clear();
(*_node_data)[index].heap.clear();
(*_node_data)[index].pot = max;
_blossom_set->insert(n, std::numeric_limits<Value>::max());
_tree_set->insert(blossom);
(*_blossom_data)[blossom].status = EVEN;
(*_blossom_data)[blossom].pred = INVALID;
(*_blossom_data)[blossom].next = INVALID;
(*_blossom_data)[blossom].pot = 0;
(*_blossom_data)[blossom].offset = 0;
for (EdgeIt e(_graph); e != INVALID; ++e) {
int si = (*_node_index)[_graph.u(e)];
int ti = (*_node_index)[_graph.v(e)];
if (_graph.u(e) != _graph.v(e)) {
_delta3->push(e, ((*_node_data)[si].pot + (*_node_data)[ti].pot -
dualScale * _weight[e]) / 2);
/// \brief Start the algorithm
/// This function starts the algorithm.
/// \pre \ref init() must be called before using this function.
int unmatched = _node_num;
Value d1 = !_delta1->empty() ?
_delta1->prio() : std::numeric_limits<Value>::max();
Value d2 = !_delta2->empty() ?
_delta2->prio() : std::numeric_limits<Value>::max();
Value d3 = !_delta3->empty() ?
_delta3->prio() : std::numeric_limits<Value>::max();
Value d4 = !_delta4->empty() ?
_delta4->prio() : std::numeric_limits<Value>::max();
_delta_sum = d1; OpType ot = D1;
if (d2 < _delta_sum) { _delta_sum = d2; ot = D2; }
if (d3 < _delta_sum) { _delta_sum = d3; ot = D3; }
if (d4 < _delta_sum) { _delta_sum = d4; ot = D4; }
int blossom = _delta2->top();
Node n = _blossom_set->classTop(blossom);
Arc e = (*_node_data)[(*_node_index)[n]].heap.top();
int left_blossom = _blossom_set->find(_graph.u(e));
int right_blossom = _blossom_set->find(_graph.v(e));
if (left_blossom == right_blossom) {
if ((*_blossom_data)[left_blossom].status == EVEN) {
left_tree = _tree_set->find(left_blossom);
if ((*_blossom_data)[right_blossom].status == EVEN) {
right_tree = _tree_set->find(right_blossom);
if (left_tree == right_tree) {
shrinkOnEdge(e, left_tree);
splitBlossom(_delta4->top());
/// \brief Run the algorithm.
/// This method runs the \c %MaxWeightedMatching algorithm.
/// \note mwm.run() is just a shortcut of the following code.
/// \name Primal Solution
/// Functions to get the primal solution, i.e. the maximum weighted
/// Either \ref run() or \ref start() function should be called before
/// \brief Return the weight of the matching.
/// This function returns the weight of the found matching.
/// \pre Either run() or start() must be called before using this function.
Value matchingWeight() const {
for (NodeIt n(_graph); n != INVALID; ++n) {
if ((*_matching)[n] != INVALID) {
sum += _weight[(*_matching)[n]];
/// \brief Return the size (cardinality) of the matching.
/// This function returns the size (cardinality) of the found matching.
/// \pre Either run() or start() must be called before using this function.
int matchingSize() const {
for (NodeIt n(_graph); n != INVALID; ++n) {
if ((*_matching)[n] != INVALID) {
/// \brief Return \c true if the given edge is in the matching.
/// This function returns \c true if the given edge is in the found
/// \pre Either run() or start() must be called before using this function.
bool matching(const Edge& edge) const {
return edge == (*_matching)[_graph.u(edge)];
/// \brief Return the matching arc (or edge) incident to the given node.
/// This function returns the matching arc (or edge) incident to the
/// given node in the found matching or \c INVALID if the node is
/// not covered by the matching.
/// \pre Either run() or start() must be called before using this function.
Arc matching(const Node& node) const {
return (*_matching)[node];
/// \brief Return a const reference to the matching map.
/// This function returns a const reference to a node map that stores
/// the matching arc (or edge) incident to each node.
const MatchingMap& matchingMap() const {
/// \brief Return the mate of the given node.
/// This function returns the mate of the given node in the found
/// matching or \c INVALID if the node is not covered by the matching.
/// \pre Either run() or start() must be called before using this function.
Node mate(const Node& node) const {
return (*_matching)[node] != INVALID ?
_graph.target((*_matching)[node]) : INVALID;
/// Functions to get the dual solution.\n
/// Either \ref run() or \ref start() function should be called before
/// \brief Return the value of the dual solution.
/// This function returns the value of the dual solution.
/// It should be equal to the primal value scaled by \ref dualScale
/// \pre Either run() or start() must be called before using this function.
Value dualValue() const {
for (NodeIt n(_graph); n != INVALID; ++n) {
for (int i = 0; i < blossomNum(); ++i) {
sum += blossomValue(i) * (blossomSize(i) / 2);
/// \brief Return the dual value (potential) of the given node.
/// This function returns the dual value (potential) of the given node.
/// \pre Either run() or start() must be called before using this function.
Value nodeValue(const Node& n) const {
return (*_node_potential)[n];
/// \brief Return the number of the blossoms in the basis.
/// This function returns the number of the blossoms in the basis.
/// \pre Either run() or start() must be called before using this function.
return _blossom_potential.size();
/// \brief Return the number of the nodes in the given blossom.
/// This function returns the number of the nodes in the given blossom.
/// \pre Either run() or start() must be called before using this function.
int blossomSize(int k) const {
return _blossom_potential[k].end - _blossom_potential[k].begin;
/// \brief Return the dual value (ptential) of the given blossom.
/// This function returns the dual value (ptential) of the given blossom.
/// \pre Either run() or start() must be called before using this function.
Value blossomValue(int k) const {
return _blossom_potential[k].value;
/// \brief Iterator for obtaining the nodes of a blossom.
/// This class provides an iterator for obtaining the nodes of the
/// given blossom. It lists a subset of the nodes.
/// Before using this iterator, you must allocate a
/// MaxWeightedMatching class and execute it.
/// Constructor to get the nodes of the given variable.
/// \pre Either \ref MaxWeightedMatching::run() "algorithm.run()" or
/// \ref MaxWeightedMatching::start() "algorithm.start()" must be
/// called before initializing this iterator.
BlossomIt(const MaxWeightedMatching& algorithm, int variable)
_index = _algorithm->_blossom_potential[variable].begin;
_last = _algorithm->_blossom_potential[variable].end;
/// \brief Conversion to \c Node.
/// Conversion to \c Node.
return _algorithm->_blossom_node_list[_index];
/// \brief Increment operator.
BlossomIt& operator++() {
/// \brief Validity checking
/// Checks whether the iterator is invalid.
bool operator==(Invalid) const { return _index == _last; }
/// \brief Validity checking
/// Checks whether the iterator is valid.
bool operator!=(Invalid) const { return _index != _last; }
const MaxWeightedMatching* _algorithm;
/// \brief Weighted perfect matching in general graphs
/// This class provides an efficient implementation of Edmond's
/// maximum weighted perfect matching algorithm. The implementation
/// is based on extensive use of priority queues and provides
/// \f$O(nm\log n)\f$ time complexity.
/// The maximum weighted perfect matching problem is to find a subset of
/// the edges in an undirected graph with maximum overall weight for which
/// each node has exactly one incident edge.
/// It can be formulated with the following linear program.
/// \f[ \sum_{e \in \delta(u)}x_e = 1 \quad \forall u\in V\f]
/** \f[ \sum_{e \in \gamma(B)}x_e \le \frac{\vert B \vert - 1}{2}
\quad \forall B\in\mathcal{O}\f] */
/// \f[x_e \ge 0\quad \forall e\in E\f]
/// \f[\max \sum_{e\in E}x_ew_e\f]
/// where \f$\delta(X)\f$ is the set of edges incident to a node in
/// \f$X\f$, \f$\gamma(X)\f$ is the set of edges with both ends in
/// \f$X\f$ and \f$\mathcal{O}\f$ is the set of odd cardinality
/// subsets of the nodes.
/// The algorithm calculates an optimal matching and a proof of the
/// optimality. The solution of the dual problem can be used to check
/// the result of the algorithm. The dual linear problem is the
/** \f[ y_u + y_v + \sum_{B \in \mathcal{O}, uv \in \gamma(B)}z_B \ge
w_{uv} \quad \forall uv\in E\f] */
/// \f[z_B \ge 0 \quad \forall B \in \mathcal{O}\f]
/** \f[\min \sum_{u \in V}y_u + \sum_{B \in \mathcal{O}}
\frac{\vert B \vert - 1}{2}z_B\f] */
/// The algorithm can be executed with the run() function.
/// After it the matching (the primal solution) and the dual solution
/// can be obtained using the query functions and the
/// \ref MaxWeightedPerfectMatching::BlossomIt "BlossomIt" nested class,
/// which is able to iterate on the nodes of a blossom.
/// If the value type is integer, then the dual solution is multiplied
/// by \ref MaxWeightedMatching::dualScale "4".
/// \tparam GR The undirected graph type the algorithm runs on.
/// \tparam WM The type edge weight map. The default type is
/// \ref concepts::Graph::EdgeMap "GR::EdgeMap<int>".
template <typename GR, typename WM>
typename WM = typename GR::template EdgeMap<int> >
class MaxWeightedPerfectMatching {
/// The graph type of the algorithm
/// The type of the edge weight map
/// The value type of the edge weights
typedef typename WeightMap::Value Value;
/// \brief Scaling factor for dual solution
/// Scaling factor for dual solution, it is equal to 4 or 1
/// according to the value type.
static const int dualScale =
std::numeric_limits<Value>::is_integer ? 4 : 1;
/// The type of the matching map
typedef typename Graph::template NodeMap<typename Graph::Arc>
TEMPLATE_GRAPH_TYPEDEFS(Graph);
typedef typename Graph::template NodeMap<Value> NodePotential;
typedef std::vector<Node> BlossomNodeList;
BlossomVariable(int _begin, int _end, Value _value)
: begin(_begin), end(_end), value(_value) {}
typedef std::vector<BlossomVariable> BlossomPotential;
const WeightMap& _weight;
NodePotential* _node_potential;
BlossomPotential _blossom_potential;
BlossomNodeList _blossom_node_list;
typedef RangeMap<int> IntIntMap;
EVEN = -1, MATCHED = 0, ODD = 1
typedef HeapUnionFind<Value, IntNodeMap> BlossomSet;
IntNodeMap *_blossom_index;
BlossomSet *_blossom_set;
RangeMap<BlossomData>* _blossom_data;
IntArcMap *_node_heap_index;
NodeData(IntArcMap& node_heap_index)
: heap(node_heap_index) {}
BinHeap<Value, IntArcMap> heap;
std::map<int, Arc> heap_index;
RangeMap<NodeData>* _node_data;
typedef ExtendFindEnum<IntIntMap> TreeSet;
IntIntMap *_tree_set_index;
IntIntMap *_delta2_index;
BinHeap<Value, IntIntMap> *_delta2;
IntEdgeMap *_delta3_index;
BinHeap<Value, IntEdgeMap> *_delta3;
IntIntMap *_delta4_index;
BinHeap<Value, IntIntMap> *_delta4;
void createStructures() {
_node_num = countNodes(_graph);
_blossom_num = _node_num * 3 / 2;
_matching = new MatchingMap(_graph);
_node_potential = new NodePotential(_graph);
_blossom_index = new IntNodeMap(_graph);
_blossom_set = new BlossomSet(*_blossom_index);
_blossom_data = new RangeMap<BlossomData>(_blossom_num);
} else if (_blossom_data->size() != _blossom_num) {
_blossom_data = new RangeMap<BlossomData>(_blossom_num);
_node_index = new IntNodeMap(_graph);
_node_heap_index = new IntArcMap(_graph);
_node_data = new RangeMap<NodeData>(_node_num,
NodeData(*_node_heap_index));
} else if (_node_data->size() != _node_num) {
_node_data = new RangeMap<NodeData>(_node_num,
NodeData(*_node_heap_index));
_tree_set_index = new IntIntMap(_blossom_num);
_tree_set = new TreeSet(*_tree_set_index);
_tree_set_index->resize(_blossom_num);
_delta2_index = new IntIntMap(_blossom_num);
_delta2 = new BinHeap<Value, IntIntMap>(*_delta2_index);
_delta2_index->resize(_blossom_num);
_delta3_index = new IntEdgeMap(_graph);
_delta3 = new BinHeap<Value, IntEdgeMap>(*_delta3_index);
_delta4_index = new IntIntMap(_blossom_num);
_delta4 = new BinHeap<Value, IntIntMap>(*_delta4_index);
_delta4_index->resize(_blossom_num);
void destroyStructures() {
_node_num = countNodes(_graph);
_blossom_num = _node_num * 3 / 2;
void matchedToEven(int blossom, int tree) {
if (_delta2->state(blossom) == _delta2->IN_HEAP) {
if (!_blossom_set->trivial(blossom)) {
(*_blossom_data)[blossom].pot -=
2 * (_delta_sum - (*_blossom_data)[blossom].offset);
for (typename BlossomSet::ItemIt n(*_blossom_set, blossom);
_blossom_set->increase(n, std::numeric_limits<Value>::max());
int ni = (*_node_index)[n];
(*_node_data)[ni].heap.clear();
(*_node_data)[ni].heap_index.clear();
(*_node_data)[ni].pot += _delta_sum - (*_blossom_data)[blossom].offset;
for (InArcIt e(_graph, n); e != INVALID; ++e) {
Node v = _graph.source(e);
int vb = _blossom_set->find(v);
int vi = (*_node_index)[v];
Value rw = (*_node_data)[ni].pot + (*_node_data)[vi].pot -
if ((*_blossom_data)[vb].status == EVEN) {
if (_delta3->state(e) != _delta3->IN_HEAP && blossom != vb) {
_delta3->push(e, rw / 2);
typename std::map<int, Arc>::iterator it =
(*_node_data)[vi].heap_index.find(tree);
if (it != (*_node_data)[vi].heap_index.end()) {
if ((*_node_data)[vi].heap[it->second] > rw) {
(*_node_data)[vi].heap.replace(it->second, e);
(*_node_data)[vi].heap.decrease(e, rw);
(*_node_data)[vi].heap.push(e, rw);
(*_node_data)[vi].heap_index.insert(std::make_pair(tree, e));
if ((*_blossom_set)[v] > (*_node_data)[vi].heap.prio()) {
_blossom_set->decrease(v, (*_node_data)[vi].heap.prio());
if ((*_blossom_data)[vb].status == MATCHED) {
if (_delta2->state(vb) != _delta2->IN_HEAP) {
_delta2->push(vb, _blossom_set->classPrio(vb) -
(*_blossom_data)[vb].offset);
} else if ((*_delta2)[vb] > _blossom_set->classPrio(vb) -
(*_blossom_data)[vb].offset){
_delta2->decrease(vb, _blossom_set->classPrio(vb) -
(*_blossom_data)[vb].offset);
(*_blossom_data)[blossom].offset = 0;
void matchedToOdd(int blossom) {
if (_delta2->state(blossom) == _delta2->IN_HEAP) {
(*_blossom_data)[blossom].offset += _delta_sum;
if (!_blossom_set->trivial(blossom)) {
_delta4->push(blossom, (*_blossom_data)[blossom].pot / 2 +
(*_blossom_data)[blossom].offset);
void evenToMatched(int blossom, int tree) {
if (!_blossom_set->trivial(blossom)) {
(*_blossom_data)[blossom].pot += 2 * _delta_sum;
for (typename BlossomSet::ItemIt n(*_blossom_set, blossom);
int ni = (*_node_index)[n];
(*_node_data)[ni].pot -= _delta_sum;
for (InArcIt e(_graph, n); e != INVALID; ++e) {
Node v = _graph.source(e);
int vb = _blossom_set->find(v);
int vi = (*_node_index)[v];
Value rw = (*_node_data)[ni].pot + (*_node_data)[vi].pot -
if (_delta3->state(e) == _delta3->IN_HEAP) {
} else if ((*_blossom_data)[vb].status == EVEN) {
if (_delta3->state(e) == _delta3->IN_HEAP) {
int vt = _tree_set->find(vb);
Arc r = _graph.oppositeArc(e);
typename std::map<int, Arc>::iterator it =
(*_node_data)[ni].heap_index.find(vt);
if (it != (*_node_data)[ni].heap_index.end()) {
if ((*_node_data)[ni].heap[it->second] > rw) {
(*_node_data)[ni].heap.replace(it->second, r);
(*_node_data)[ni].heap.decrease(r, rw);
(*_node_data)[ni].heap.push(r, rw);
(*_node_data)[ni].heap_index.insert(std::make_pair(vt, r));
if ((*_blossom_set)[n] > (*_node_data)[ni].heap.prio()) {
_blossom_set->decrease(n, (*_node_data)[ni].heap.prio());
if (_delta2->state(blossom) != _delta2->IN_HEAP) {
_delta2->push(blossom, _blossom_set->classPrio(blossom) -
(*_blossom_data)[blossom].offset);
} else if ((*_delta2)[blossom] >
_blossom_set->classPrio(blossom) -
(*_blossom_data)[blossom].offset){
_delta2->decrease(blossom, _blossom_set->classPrio(blossom) -
(*_blossom_data)[blossom].offset);
typename std::map<int, Arc>::iterator it =
(*_node_data)[vi].heap_index.find(tree);
if (it != (*_node_data)[vi].heap_index.end()) {
(*_node_data)[vi].heap.erase(it->second);
(*_node_data)[vi].heap_index.erase(it);
if ((*_node_data)[vi].heap.empty()) {
_blossom_set->increase(v, std::numeric_limits<Value>::max());
} else if ((*_blossom_set)[v] < (*_node_data)[vi].heap.prio()) {
_blossom_set->increase(v, (*_node_data)[vi].heap.prio());
if ((*_blossom_data)[vb].status == MATCHED) {
if (_blossom_set->classPrio(vb) ==
std::numeric_limits<Value>::max()) {
} else if ((*_delta2)[vb] < _blossom_set->classPrio(vb) -
(*_blossom_data)[vb].offset) {
_delta2->increase(vb, _blossom_set->classPrio(vb) -
(*_blossom_data)[vb].offset);
void oddToMatched(int blossom) {
(*_blossom_data)[blossom].offset -= _delta_sum;
if (_blossom_set->classPrio(blossom) !=
std::numeric_limits<Value>::max()) {
_delta2->push(blossom, _blossom_set->classPrio(blossom) -
(*_blossom_data)[blossom].offset);
if (!_blossom_set->trivial(blossom)) {
void oddToEven(int blossom, int tree) {
if (!_blossom_set->trivial(blossom)) {
(*_blossom_data)[blossom].pot -=
2 * (2 * _delta_sum - (*_blossom_data)[blossom].offset);
for (typename BlossomSet::ItemIt n(*_blossom_set, blossom);
int ni = (*_node_index)[n];
_blossom_set->increase(n, std::numeric_limits<Value>::max());
(*_node_data)[ni].heap.clear();
(*_node_data)[ni].heap_index.clear();
2 * _delta_sum - (*_blossom_data)[blossom].offset;
for (InArcIt e(_graph, n); e != INVALID; ++e) {
Node v = _graph.source(e);
int vb = _blossom_set->find(v);
int vi = (*_node_index)[v];
Value rw = (*_node_data)[ni].pot + (*_node_data)[vi].pot -
if ((*_blossom_data)[vb].status == EVEN) {
if (_delta3->state(e) != _delta3->IN_HEAP && blossom != vb) {
_delta3->push(e, rw / 2);
typename std::map<int, Arc>::iterator it =
(*_node_data)[vi].heap_index.find(tree);
if (it != (*_node_data)[vi].heap_index.end()) {
if ((*_node_data)[vi].heap[it->second] > rw) {
(*_node_data)[vi].heap.replace(it->second, e);
(*_node_data)[vi].heap.decrease(e, rw);
(*_node_data)[vi].heap.push(e, rw);
(*_node_data)[vi].heap_index.insert(std::make_pair(tree, e));
if ((*_blossom_set)[v] > (*_node_data)[vi].heap.prio()) {
_blossom_set->decrease(v, (*_node_data)[vi].heap.prio());
if ((*_blossom_data)[vb].status == MATCHED) {
if (_delta2->state(vb) != _delta2->IN_HEAP) {
_delta2->push(vb, _blossom_set->classPrio(vb) -
(*_blossom_data)[vb].offset);
} else if ((*_delta2)[vb] > _blossom_set->classPrio(vb) -
(*_blossom_data)[vb].offset) {
_delta2->decrease(vb, _blossom_set->classPrio(vb) -
(*_blossom_data)[vb].offset);
(*_blossom_data)[blossom].offset = 0;
void alternatePath(int even, int tree) {
evenToMatched(even, tree);
(*_blossom_data)[even].status = MATCHED;
while ((*_blossom_data)[even].pred != INVALID) {
odd = _blossom_set->find(_graph.target((*_blossom_data)[even].pred));
(*_blossom_data)[odd].status = MATCHED;
(*_blossom_data)[odd].next = (*_blossom_data)[odd].pred;
even = _blossom_set->find(_graph.target((*_blossom_data)[odd].pred));
(*_blossom_data)[even].status = MATCHED;
evenToMatched(even, tree);
(*_blossom_data)[even].next =
_graph.oppositeArc((*_blossom_data)[odd].pred);
void destroyTree(int tree) {
for (TreeSet::ItemIt b(*_tree_set, tree); b != INVALID; ++b) {
if ((*_blossom_data)[b].status == EVEN) {
(*_blossom_data)[b].status = MATCHED;
} else if ((*_blossom_data)[b].status == ODD) {
(*_blossom_data)[b].status = MATCHED;
_tree_set->eraseClass(tree);
void augmentOnEdge(const Edge& edge) {
int left = _blossom_set->find(_graph.u(edge));
int right = _blossom_set->find(_graph.v(edge));
int left_tree = _tree_set->find(left);
alternatePath(left, left_tree);
int right_tree = _tree_set->find(right);
alternatePath(right, right_tree);
(*_blossom_data)[left].next = _graph.direct(edge, true);
(*_blossom_data)[right].next = _graph.direct(edge, false);
void extendOnArc(const Arc& arc) {
int base = _blossom_set->find(_graph.target(arc));
int tree = _tree_set->find(base);
int odd = _blossom_set->find(_graph.source(arc));
_tree_set->insert(odd, tree);
(*_blossom_data)[odd].status = ODD;
(*_blossom_data)[odd].pred = arc;
int even = _blossom_set->find(_graph.target((*_blossom_data)[odd].next));
(*_blossom_data)[even].pred = (*_blossom_data)[even].next;
_tree_set->insert(even, tree);
(*_blossom_data)[even].status = EVEN;
matchedToEven(even, tree);
void shrinkOnEdge(const Edge& edge, int tree) {
std::vector<int> left_path, right_path;
std::set<int> left_set, right_set;
int left = _blossom_set->find(_graph.u(edge));
left_path.push_back(left);
int right = _blossom_set->find(_graph.v(edge));
right_path.push_back(right);
if ((*_blossom_data)[left].pred == INVALID) break;
_blossom_set->find(_graph.target((*_blossom_data)[left].pred));
left_path.push_back(left);
_blossom_set->find(_graph.target((*_blossom_data)[left].pred));
left_path.push_back(left);
if (right_set.find(left) != right_set.end()) {
if ((*_blossom_data)[right].pred == INVALID) break;
_blossom_set->find(_graph.target((*_blossom_data)[right].pred));
right_path.push_back(right);
_blossom_set->find(_graph.target((*_blossom_data)[right].pred));
right_path.push_back(right);
if (left_set.find(right) != left_set.end()) {
if ((*_blossom_data)[left].pred == INVALID) {
while (left_set.find(nca) == left_set.end()) {
_blossom_set->find(_graph.target((*_blossom_data)[nca].pred));
right_path.push_back(nca);
_blossom_set->find(_graph.target((*_blossom_data)[nca].pred));
right_path.push_back(nca);
while (right_set.find(nca) == right_set.end()) {
_blossom_set->find(_graph.target((*_blossom_data)[nca].pred));
left_path.push_back(nca);
_blossom_set->find(_graph.target((*_blossom_data)[nca].pred));
left_path.push_back(nca);
std::vector<int> subblossoms;
prev = _graph.direct(edge, true);
for (int i = 0; left_path[i] != nca; i += 2) {
subblossoms.push_back(left_path[i]);
(*_blossom_data)[left_path[i]].next = prev;
_tree_set->erase(left_path[i]);
subblossoms.push_back(left_path[i + 1]);
(*_blossom_data)[left_path[i + 1]].status = EVEN;
oddToEven(left_path[i + 1], tree);
_tree_set->erase(left_path[i + 1]);
prev = _graph.oppositeArc((*_blossom_data)[left_path[i + 1]].pred);
while (right_path[k] != nca) ++k;
subblossoms.push_back(nca);
(*_blossom_data)[nca].next = prev;
for (int i = k - 2; i >= 0; i -= 2) {
subblossoms.push_back(right_path[i + 1]);
(*_blossom_data)[right_path[i + 1]].status = EVEN;
oddToEven(right_path[i + 1], tree);
_tree_set->erase(right_path[i + 1]);
(*_blossom_data)[right_path[i + 1]].next =
(*_blossom_data)[right_path[i + 1]].pred;
subblossoms.push_back(right_path[i]);
_tree_set->erase(right_path[i]);
_blossom_set->join(subblossoms.begin(), subblossoms.end());
for (int i = 0; i < int(subblossoms.size()); ++i) {
if (!_blossom_set->trivial(subblossoms[i])) {
(*_blossom_data)[subblossoms[i]].pot += 2 * _delta_sum;
(*_blossom_data)[subblossoms[i]].status = MATCHED;
(*_blossom_data)[surface].pot = -2 * _delta_sum;
(*_blossom_data)[surface].offset = 0;
(*_blossom_data)[surface].status = EVEN;
(*_blossom_data)[surface].pred = (*_blossom_data)[nca].pred;
(*_blossom_data)[surface].next = (*_blossom_data)[nca].pred;
_tree_set->insert(surface, tree);
void splitBlossom(int blossom) {
Arc next = (*_blossom_data)[blossom].next;
Arc pred = (*_blossom_data)[blossom].pred;
int tree = _tree_set->find(blossom);
(*_blossom_data)[blossom].status = MATCHED;
if (_delta2->state(blossom) == _delta2->IN_HEAP) {
std::vector<int> subblossoms;
_blossom_set->split(blossom, std::back_inserter(subblossoms));
Value offset = (*_blossom_data)[blossom].offset;
int b = _blossom_set->find(_graph.source(pred));
int d = _blossom_set->find(_graph.source(next));
for (int i = 0; i < int(subblossoms.size()); ++i) {
if (subblossoms[i] == b) ib = i;
if (subblossoms[i] == d) id = i;
(*_blossom_data)[subblossoms[i]].offset = offset;
if (!_blossom_set->trivial(subblossoms[i])) {
(*_blossom_data)[subblossoms[i]].pot -= 2 * offset;
if (_blossom_set->classPrio(subblossoms[i]) !=
std::numeric_limits<Value>::max()) {
_delta2->push(subblossoms[i],
_blossom_set->classPrio(subblossoms[i]) -
(*_blossom_data)[subblossoms[i]].offset);
if (id > ib ? ((id - ib) % 2 == 0) : ((ib - id) % 2 == 1)) {
for (int i = (id + 1) % subblossoms.size();
i != ib; i = (i + 2) % subblossoms.size()) {
int tb = subblossoms[(i + 1) % subblossoms.size()];
(*_blossom_data)[sb].next =
_graph.oppositeArc((*_blossom_data)[tb].next);
for (int i = ib; i != id; i = (i + 2) % subblossoms.size()) {
int tb = subblossoms[(i + 1) % subblossoms.size()];
int ub = subblossoms[(i + 2) % subblossoms.size()];
(*_blossom_data)[sb].status = ODD;
_tree_set->insert(sb, tree);
(*_blossom_data)[sb].pred = pred;
(*_blossom_data)[sb].next =
_graph.oppositeArc((*_blossom_data)[tb].next);
pred = (*_blossom_data)[ub].next;
(*_blossom_data)[tb].status = EVEN;
_tree_set->insert(tb, tree);
(*_blossom_data)[tb].pred = (*_blossom_data)[tb].next;
(*_blossom_data)[subblossoms[id]].status = ODD;
matchedToOdd(subblossoms[id]);
_tree_set->insert(subblossoms[id], tree);
(*_blossom_data)[subblossoms[id]].next = next;
(*_blossom_data)[subblossoms[id]].pred = pred;
for (int i = (ib + 1) % subblossoms.size();
i != id; i = (i + 2) % subblossoms.size()) {
int tb = subblossoms[(i + 1) % subblossoms.size()];
(*_blossom_data)[sb].next =
_graph.oppositeArc((*_blossom_data)[tb].next);
for (int i = id; i != ib; i = (i + 2) % subblossoms.size()) {
int tb = subblossoms[(i + 1) % subblossoms.size()];
int ub = subblossoms[(i + 2) % subblossoms.size()];
(*_blossom_data)[sb].status = ODD;
_tree_set->insert(sb, tree);
(*_blossom_data)[sb].next = next;
(*_blossom_data)[sb].pred =
_graph.oppositeArc((*_blossom_data)[tb].next);
(*_blossom_data)[tb].status = EVEN;
_tree_set->insert(tb, tree);
(*_blossom_data)[tb].pred =
(*_blossom_data)[tb].next =
_graph.oppositeArc((*_blossom_data)[ub].next);
next = (*_blossom_data)[ub].next;
(*_blossom_data)[subblossoms[ib]].status = ODD;
matchedToOdd(subblossoms[ib]);
_tree_set->insert(subblossoms[ib], tree);
(*_blossom_data)[subblossoms[ib]].next = next;
(*_blossom_data)[subblossoms[ib]].pred = pred;
_tree_set->erase(blossom);
void extractBlossom(int blossom, const Node& base, const Arc& matching) {
if (_blossom_set->trivial(blossom)) {
int bi = (*_node_index)[base];
Value pot = (*_node_data)[bi].pot;
(*_matching)[base] = matching;
_blossom_node_list.push_back(base);
(*_node_potential)[base] = pot;
Value pot = (*_blossom_data)[blossom].pot;
int bn = _blossom_node_list.size();
std::vector<int> subblossoms;
_blossom_set->split(blossom, std::back_inserter(subblossoms));
int b = _blossom_set->find(base);
for (int i = 0; i < int(subblossoms.size()); ++i) {
if (subblossoms[i] == b) { ib = i; break; }
for (int i = 1; i < int(subblossoms.size()); i += 2) {
int sb = subblossoms[(ib + i) % subblossoms.size()];
int tb = subblossoms[(ib + i + 1) % subblossoms.size()];
Arc m = (*_blossom_data)[tb].next;
extractBlossom(sb, _graph.target(m), _graph.oppositeArc(m));
extractBlossom(tb, _graph.source(m), m);
extractBlossom(subblossoms[ib], base, matching);
int en = _blossom_node_list.size();
_blossom_potential.push_back(BlossomVariable(bn, en, pot));
std::vector<int> blossoms;
for (typename BlossomSet::ClassIt c(*_blossom_set); c != INVALID; ++c) {
for (int i = 0; i < int(blossoms.size()); ++i) {
Value offset = (*_blossom_data)[blossoms[i]].offset;
(*_blossom_data)[blossoms[i]].pot += 2 * offset;
for (typename BlossomSet::ItemIt n(*_blossom_set, blossoms[i]);
(*_node_data)[(*_node_index)[n]].pot -= offset;
Arc matching = (*_blossom_data)[blossoms[i]].next;
Node base = _graph.source(matching);
extractBlossom(blossoms[i], base, matching);
MaxWeightedPerfectMatching(const Graph& graph, const WeightMap& weight)
: _graph(graph), _weight(weight), _matching(0),
_node_potential(0), _blossom_potential(), _blossom_node_list(),
_node_num(0), _blossom_num(0),
_blossom_index(0), _blossom_set(0), _blossom_data(0),
_node_index(0), _node_heap_index(0), _node_data(0),
_tree_set_index(0), _tree_set(0),
_delta2_index(0), _delta2(0),
_delta3_index(0), _delta3(0),
_delta4_index(0), _delta4(0),
~MaxWeightedPerfectMatching() {
/// \name Execution Control
/// The simplest way to execute the algorithm is to use the
/// \ref run() member function.
/// \brief Initialize the algorithm
/// This function initializes the algorithm.
_blossom_node_list.clear();
_blossom_potential.clear();
for (ArcIt e(_graph); e != INVALID; ++e) {
(*_node_heap_index)[e] = BinHeap<Value, IntArcMap>::PRE_HEAP;
for (EdgeIt e(_graph); e != INVALID; ++e) {
(*_delta3_index)[e] = _delta3->PRE_HEAP;
for (int i = 0; i < _blossom_num; ++i) {
(*_delta2_index)[i] = _delta2->PRE_HEAP;
(*_delta4_index)[i] = _delta4->PRE_HEAP;
for (NodeIt n(_graph); n != INVALID; ++n) {
Value max = - std::numeric_limits<Value>::max();
for (OutArcIt e(_graph, n); e != INVALID; ++e) {
if (_graph.target(e) == n) continue;
if ((dualScale * _weight[e]) / 2 > max) {
max = (dualScale * _weight[e]) / 2;
(*_node_index)[n] = index;
(*_node_data)[index].heap_index.clear();
(*_node_data)[index].heap.clear();
(*_node_data)[index].pot = max;
_blossom_set->insert(n, std::numeric_limits<Value>::max());
_tree_set->insert(blossom);
(*_blossom_data)[blossom].status = EVEN;
(*_blossom_data)[blossom].pred = INVALID;
(*_blossom_data)[blossom].next = INVALID;
(*_blossom_data)[blossom].pot = 0;
(*_blossom_data)[blossom].offset = 0;
for (EdgeIt e(_graph); e != INVALID; ++e) {
int si = (*_node_index)[_graph.u(e)];
int ti = (*_node_index)[_graph.v(e)];
if (_graph.u(e) != _graph.v(e)) {
_delta3->push(e, ((*_node_data)[si].pot + (*_node_data)[ti].pot -
dualScale * _weight[e]) / 2);
/// \brief Start the algorithm
/// This function starts the algorithm.
/// \pre \ref init() must be called before using this function.
int unmatched = _node_num;
Value d2 = !_delta2->empty() ?
_delta2->prio() : std::numeric_limits<Value>::max();
Value d3 = !_delta3->empty() ?
_delta3->prio() : std::numeric_limits<Value>::max();
Value d4 = !_delta4->empty() ?
_delta4->prio() : std::numeric_limits<Value>::max();
_delta_sum = d2; OpType ot = D2;
if (d3 < _delta_sum) { _delta_sum = d3; ot = D3; }
if (d4 < _delta_sum) { _delta_sum = d4; ot = D4; }
if (_delta_sum == std::numeric_limits<Value>::max()) {
int blossom = _delta2->top();
Node n = _blossom_set->classTop(blossom);
Arc e = (*_node_data)[(*_node_index)[n]].heap.top();
int left_blossom = _blossom_set->find(_graph.u(e));
int right_blossom = _blossom_set->find(_graph.v(e));
if (left_blossom == right_blossom) {
int left_tree = _tree_set->find(left_blossom);
int right_tree = _tree_set->find(right_blossom);
if (left_tree == right_tree) {
shrinkOnEdge(e, left_tree);
splitBlossom(_delta4->top());
/// \brief Run the algorithm.
/// This method runs the \c %MaxWeightedPerfectMatching algorithm.
/// \note mwpm.run() is just a shortcut of the following code.
/// \name Primal Solution
/// Functions to get the primal solution, i.e. the maximum weighted
/// Either \ref run() or \ref start() function should be called before
/// \brief Return the weight of the matching.
/// This function returns the weight of the found matching.
/// \pre Either run() or start() must be called before using this function.
Value matchingWeight() const {
for (NodeIt n(_graph); n != INVALID; ++n) {
if ((*_matching)[n] != INVALID) {
sum += _weight[(*_matching)[n]];
/// \brief Return \c true if the given edge is in the matching.
/// This function returns \c true if the given edge is in the found
/// \pre Either run() or start() must be called before using this function.
bool matching(const Edge& edge) const {
return static_cast<const Edge&>((*_matching)[_graph.u(edge)]) == edge;
/// \brief Return the matching arc (or edge) incident to the given node.
/// This function returns the matching arc (or edge) incident to the
/// given node in the found matching or \c INVALID if the node is
/// not covered by the matching.
/// \pre Either run() or start() must be called before using this function.
Arc matching(const Node& node) const {
return (*_matching)[node];
/// \brief Return a const reference to the matching map.
/// This function returns a const reference to a node map that stores
/// the matching arc (or edge) incident to each node.
const MatchingMap& matchingMap() const {
/// \brief Return the mate of the given node.
/// This function returns the mate of the given node in the found
/// matching or \c INVALID if the node is not covered by the matching.
/// \pre Either run() or start() must be called before using this function.
Node mate(const Node& node) const {
return _graph.target((*_matching)[node]);
/// Functions to get the dual solution.\n
/// Either \ref run() or \ref start() function should be called before
/// \brief Return the value of the dual solution.
/// This function returns the value of the dual solution.
/// It should be equal to the primal value scaled by \ref dualScale
/// \pre Either run() or start() must be called before using this function.
Value dualValue() const {
for (NodeIt n(_graph); n != INVALID; ++n) {
for (int i = 0; i < blossomNum(); ++i) {
sum += blossomValue(i) * (blossomSize(i) / 2);
/// \brief Return the dual value (potential) of the given node.
/// This function returns the dual value (potential) of the given node.
/// \pre Either run() or start() must be called before using this function.
Value nodeValue(const Node& n) const {
return (*_node_potential)[n];
/// \brief Return the number of the blossoms in the basis.
/// This function returns the number of the blossoms in the basis.
/// \pre Either run() or start() must be called before using this function.
return _blossom_potential.size();
/// \brief Return the number of the nodes in the given blossom.
/// This function returns the number of the nodes in the given blossom.
/// \pre Either run() or start() must be called before using this function.
int blossomSize(int k) const {
return _blossom_potential[k].end - _blossom_potential[k].begin;
/// \brief Return the dual value (ptential) of the given blossom.
/// This function returns the dual value (ptential) of the given blossom.
/// \pre Either run() or start() must be called before using this function.
Value blossomValue(int k) const {
return _blossom_potential[k].value;
/// \brief Iterator for obtaining the nodes of a blossom.
/// This class provides an iterator for obtaining the nodes of the
/// given blossom. It lists a subset of the nodes.
/// Before using this iterator, you must allocate a
/// MaxWeightedPerfectMatching class and execute it.
/// Constructor to get the nodes of the given variable.
/// \pre Either \ref MaxWeightedPerfectMatching::run() "algorithm.run()"
/// or \ref MaxWeightedPerfectMatching::start() "algorithm.start()"
/// must be called before initializing this iterator.
BlossomIt(const MaxWeightedPerfectMatching& algorithm, int variable)
_index = _algorithm->_blossom_potential[variable].begin;
_last = _algorithm->_blossom_potential[variable].end;
/// \brief Conversion to \c Node.
/// Conversion to \c Node.
return _algorithm->_blossom_node_list[_index];
/// \brief Increment operator.
BlossomIt& operator++() {
/// \brief Validity checking
/// This function checks whether the iterator is invalid.
bool operator==(Invalid) const { return _index == _last; }
/// \brief Validity checking
/// This function checks whether the iterator is valid.
bool operator!=(Invalid) const { return _index != _last; }
const MaxWeightedPerfectMatching* _algorithm;
} //END OF NAMESPACE LEMON
#endif //LEMON_MAX_MATCHING_H