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/* -*- mode: C++; indent-tabs-mode: nil; -*- |
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* |
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* This file is a part of LEMON, a generic C++ optimization library. |
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* |
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* Copyright (C) 2003-2010 |
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* Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport |
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* (Egervary Research Group on Combinatorial Optimization, EGRES). |
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* |
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* Permission to use, modify and distribute this software is granted |
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* provided that this copyright notice appears in all copies. For |
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* precise terms see the accompanying LICENSE file. |
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* |
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* This software is provided "AS IS" with no warranty of any kind, |
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* express or implied, and with no claim as to its suitability for any |
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* purpose. |
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* |
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*/ |
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|
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#ifndef LEMON_HAO_ORLIN_H |
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#define LEMON_HAO_ORLIN_H |
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|
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#include <vector> |
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#include <list> |
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#include <limits> |
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|
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#include <lemon/maps.h> |
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#include <lemon/core.h> |
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#include <lemon/tolerance.h> |
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|
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/// \file |
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/// \ingroup min_cut |
32 | 32 |
/// \brief Implementation of the Hao-Orlin algorithm. |
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/// |
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/// Implementation of the Hao-Orlin algorithm for finding a minimum cut |
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/// in a digraph. |
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|
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namespace lemon { |
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|
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/// \ingroup min_cut |
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/// |
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/// \brief Hao-Orlin algorithm for finding a minimum cut in a digraph. |
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/// |
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/// This class implements the Hao-Orlin algorithm for finding a minimum |
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/// value cut in a directed graph \f$D=(V,A)\f$. |
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/// It takes a fixed node \f$ source \in V \f$ and |
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/// consists of two phases: in the first phase it determines a |
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/// minimum cut with \f$ source \f$ on the source-side (i.e. a set |
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/// \f$ X\subsetneq V \f$ with \f$ source \in X \f$ and minimal outgoing |
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/// capacity) and in the second phase it determines a minimum cut |
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/// with \f$ source \f$ on the sink-side (i.e. a set |
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/// \f$ X\subsetneq V \f$ with \f$ source \notin X \f$ and minimal outgoing |
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/// capacity). Obviously, the smaller of these two cuts will be a |
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/// minimum cut of \f$ D \f$. The algorithm is a modified |
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/// preflow push-relabel algorithm. Our implementation calculates |
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/// the minimum cut in \f$ O(n^2\sqrt{m}) \f$ time (we use the |
56 |
/// highest-label rule), or in \f$O(nm)\f$ for unit capacities. The |
|
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/// purpose of such algorithm is e.g. testing network reliability. |
|
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/// highest-label rule), or in \f$O(nm)\f$ for unit capacities. A notable |
|
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/// use of this algorithm is testing network reliability. |
|
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/// |
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/// For an undirected graph you can run just the first phase of the |
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/// algorithm or you can use the algorithm of Nagamochi and Ibaraki, |
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/// which solves the undirected problem in \f$ O(nm + n^2 \log n) \f$ |
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/// time. It is implemented in the NagamochiIbaraki algorithm class. |
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/// |
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/// \tparam GR The type of the digraph the algorithm runs on. |
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/// \tparam CAP The type of the arc map containing the capacities, |
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/// which can be any numreric type. The default map type is |
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/// \ref concepts::Digraph::ArcMap "GR::ArcMap<int>". |
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/// \tparam TOL Tolerance class for handling inexact computations. The |
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/// default tolerance type is \ref Tolerance "Tolerance<CAP::Value>". |
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#ifdef DOXYGEN |
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template <typename GR, typename CAP, typename TOL> |
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#else |
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template <typename GR, |
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typename CAP = typename GR::template ArcMap<int>, |
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typename TOL = Tolerance<typename CAP::Value> > |
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#endif |
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class HaoOrlin { |
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public: |
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|
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/// The digraph type of the algorithm |
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typedef GR Digraph; |
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/// The capacity map type of the algorithm |
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typedef CAP CapacityMap; |
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/// The tolerance type of the algorithm |
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typedef TOL Tolerance; |
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|
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private: |
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|
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typedef typename CapacityMap::Value Value; |
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|
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TEMPLATE_DIGRAPH_TYPEDEFS(Digraph); |
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|
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const Digraph& _graph; |
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const CapacityMap* _capacity; |
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|
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typedef typename Digraph::template ArcMap<Value> FlowMap; |
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FlowMap* _flow; |
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|
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Node _source; |
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|
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int _node_num; |
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|
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// Bucketing structure |
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std::vector<Node> _first, _last; |
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typename Digraph::template NodeMap<Node>* _next; |
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typename Digraph::template NodeMap<Node>* _prev; |
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typename Digraph::template NodeMap<bool>* _active; |
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typename Digraph::template NodeMap<int>* _bucket; |
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|
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std::vector<bool> _dormant; |
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|
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std::list<std::list<int> > _sets; |
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std::list<int>::iterator _highest; |
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|
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typedef typename Digraph::template NodeMap<Value> ExcessMap; |
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ExcessMap* _excess; |
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|
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typedef typename Digraph::template NodeMap<bool> SourceSetMap; |
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SourceSetMap* _source_set; |
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|
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Value _min_cut; |
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|
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typedef typename Digraph::template NodeMap<bool> MinCutMap; |
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MinCutMap* _min_cut_map; |
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|
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Tolerance _tolerance; |
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|
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public: |
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|
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/// \brief Constructor |
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/// |
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/// Constructor of the algorithm class. |
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HaoOrlin(const Digraph& graph, const CapacityMap& capacity, |
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const Tolerance& tolerance = Tolerance()) : |
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_graph(graph), _capacity(&capacity), _flow(0), _source(), |
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_node_num(), _first(), _last(), _next(0), _prev(0), |
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_active(0), _bucket(0), _dormant(), _sets(), _highest(), |
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_excess(0), _source_set(0), _min_cut(), _min_cut_map(0), |
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_tolerance(tolerance) {} |
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|
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~HaoOrlin() { |
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if (_min_cut_map) { |
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delete _min_cut_map; |
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} |
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if (_source_set) { |
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delete _source_set; |
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} |
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if (_excess) { |
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delete _excess; |
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} |
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if (_next) { |
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delete _next; |
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} |
... | ... |
@@ -819,187 +819,197 @@ |
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if (!_tolerance.positive(rem)) continue; |
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Node v = _graph.target(a); |
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if (!(*_active)[v] && !(*_source_set)[v]) { |
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activate(v); |
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} |
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(*_excess)[v] += rem; |
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(*_flow)[a] = 0; |
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} |
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|
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target = new_target; |
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if ((*_active)[target]) { |
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deactivate(target); |
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} |
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|
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_highest = _sets.back().begin(); |
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while (_highest != _sets.back().end() && |
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!(*_active)[_first[*_highest]]) { |
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++_highest; |
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} |
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} |
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} |
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} |
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|
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public: |
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|
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/// \name Execution Control |
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/// The simplest way to execute the algorithm is to use |
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/// one of the member functions called \ref run(). |
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/// \n |
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/// If you need better control on the execution, |
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/// you have to call one of the \ref init() functions first, then |
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/// \ref calculateOut() and/or \ref calculateIn(). |
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|
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/// @{ |
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|
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/// \brief Initialize the internal data structures. |
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/// |
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/// This function initializes the internal data structures. It creates |
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/// the maps and some bucket structures for the algorithm. |
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/// The first node is used as the source node for the push-relabel |
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/// algorithm. |
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void init() { |
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init(NodeIt(_graph)); |
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} |
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|
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/// \brief Initialize the internal data structures. |
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/// |
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/// This function initializes the internal data structures. It creates |
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/// the maps and some bucket structures for the algorithm. |
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/// The given node is used as the source node for the push-relabel |
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/// algorithm. |
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void init(const Node& source) { |
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_source = source; |
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|
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_node_num = countNodes(_graph); |
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|
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_first.resize(_node_num); |
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_last.resize(_node_num); |
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|
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_dormant.resize(_node_num); |
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|
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if (!_flow) { |
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_flow = new FlowMap(_graph); |
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} |
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if (!_next) { |
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_next = new typename Digraph::template NodeMap<Node>(_graph); |
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} |
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if (!_prev) { |
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_prev = new typename Digraph::template NodeMap<Node>(_graph); |
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} |
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if (!_active) { |
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_active = new typename Digraph::template NodeMap<bool>(_graph); |
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} |
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if (!_bucket) { |
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_bucket = new typename Digraph::template NodeMap<int>(_graph); |
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} |
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if (!_excess) { |
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_excess = new ExcessMap(_graph); |
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} |
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if (!_source_set) { |
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_source_set = new SourceSetMap(_graph); |
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} |
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if (!_min_cut_map) { |
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_min_cut_map = new MinCutMap(_graph); |
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} |
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|
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_min_cut = std::numeric_limits<Value>::max(); |
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} |
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|
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|
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/// \brief Calculate a minimum cut with \f$ source \f$ on the |
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/// source-side. |
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/// |
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/// This function calculates a minimum cut with \f$ source \f$ on the |
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/// source-side (i.e. a set \f$ X\subsetneq V \f$ with |
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/// \f$ source \in X \f$ and minimal outgoing capacity). |
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/// It updates the stored cut if (and only if) the newly found one |
|
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/// is better. |
|
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/// |
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/// \pre \ref init() must be called before using this function. |
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void calculateOut() { |
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findMinCutOut(); |
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} |
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|
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/// \brief Calculate a minimum cut with \f$ source \f$ on the |
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/// sink-side. |
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/// |
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/// This function calculates a minimum cut with \f$ source \f$ on the |
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/// sink-side (i.e. a set \f$ X\subsetneq V \f$ with |
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/// \f$ source \notin X \f$ and minimal outgoing capacity). |
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/// It updates the stored cut if (and only if) the newly found one |
|
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/// is better. |
|
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/// |
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/// \pre \ref init() must be called before using this function. |
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void calculateIn() { |
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findMinCutIn(); |
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} |
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|
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|
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/// \brief Run the algorithm. |
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/// |
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/// This function runs the algorithm. It finds nodes \c source and |
|
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/// \c target arbitrarily and then calls \ref init(), \ref calculateOut() |
|
940 |
/// This function runs the algorithm. It chooses source node, |
|
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/// then calls \ref init(), \ref calculateOut() |
|
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/// and \ref calculateIn(). |
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void run() { |
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init(); |
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calculateOut(); |
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calculateIn(); |
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} |
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|
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/// \brief Run the algorithm. |
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/// |
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/// This function runs the algorithm. It uses the given \c source node, |
|
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/// finds a proper \c target node and then calls the \ref init(), |
|
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/// |
|
951 |
/// This function runs the algorithm. It calls \ref init(), |
|
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/// \ref calculateOut() and \ref calculateIn() with the given |
|
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/// source node. |
|
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void run(const Node& s) { |
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init(s); |
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calculateOut(); |
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calculateIn(); |
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} |
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|
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/// @} |
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|
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/// \name Query Functions |
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/// The result of the %HaoOrlin algorithm |
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/// can be obtained using these functions.\n |
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/// \ref run(), \ref calculateOut() or \ref calculateIn() |
962 | 966 |
/// should be called before using them. |
963 | 967 |
|
964 | 968 |
/// @{ |
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|
966 | 970 |
/// \brief Return the value of the minimum cut. |
967 | 971 |
/// |
968 |
/// This function returns the value of the |
|
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/// This function returns the value of the best cut found by the |
|
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/// previously called \ref run(), \ref calculateOut() or \ref |
|
974 |
/// calculateIn(). |
|
969 | 975 |
/// |
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/// \pre \ref run(), \ref calculateOut() or \ref calculateIn() |
971 | 977 |
/// must be called before using this function. |
972 | 978 |
Value minCutValue() const { |
973 | 979 |
return _min_cut; |
974 | 980 |
} |
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|
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|
977 | 983 |
/// \brief Return a minimum cut. |
978 | 984 |
/// |
979 |
/// This function sets \c cutMap to the characteristic vector of a |
|
980 |
/// minimum value cut: it will give a non-empty set \f$ X\subsetneq V \f$ |
|
981 |
/// |
|
985 |
/// This function gives the best cut found by the |
|
986 |
/// previously called \ref run(), \ref calculateOut() or \ref |
|
987 |
/// calculateIn(). |
|
988 |
/// |
|
989 |
/// It sets \c cutMap to the characteristic vector of the found |
|
990 |
/// minimum value cut - a non-empty set \f$ X\subsetneq V \f$ |
|
991 |
/// of minimum outgoing capacity (i.e. \c cutMap will be \c true exactly |
|
982 | 992 |
/// for the nodes of \f$ X \f$). |
983 | 993 |
/// |
984 | 994 |
/// \param cutMap A \ref concepts::WriteMap "writable" node map with |
985 | 995 |
/// \c bool (or convertible) value type. |
986 | 996 |
/// |
987 | 997 |
/// \return The value of the minimum cut. |
988 | 998 |
/// |
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/// \pre \ref run(), \ref calculateOut() or \ref calculateIn() |
990 | 1000 |
/// must be called before using this function. |
991 | 1001 |
template <typename CutMap> |
992 | 1002 |
Value minCutMap(CutMap& cutMap) const { |
993 | 1003 |
for (NodeIt it(_graph); it != INVALID; ++it) { |
994 | 1004 |
cutMap.set(it, (*_min_cut_map)[it]); |
995 | 1005 |
} |
996 | 1006 |
return _min_cut; |
997 | 1007 |
} |
998 | 1008 |
|
999 | 1009 |
/// @} |
1000 | 1010 |
|
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}; //class HaoOrlin |
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|
1003 | 1013 |
} //namespace lemon |
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|
1005 | 1015 |
#endif //LEMON_HAO_ORLIN_H |
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