/* -*- mode: C++; indent-tabs-mode: nil; -*- * * This file is a part of LEMON, a generic C++ optimization library. * * Copyright (C) 2003-2010 * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport * (Egervary Research Group on Combinatorial Optimization, EGRES). * * Permission to use, modify and distribute this software is granted * provided that this copyright notice appears in all copies. For * precise terms see the accompanying LICENSE file. * * This software is provided "AS IS" with no warranty of any kind, * express or implied, and with no claim as to its suitability for any * purpose. * */ #ifndef LEMON_EDMONDS_KARP_H #define LEMON_EDMONDS_KARP_H /// \file /// \ingroup max_flow /// \brief Implementation of the Edmonds-Karp algorithm. #include #include namespace lemon { /// \brief Default traits class of EdmondsKarp class. /// /// Default traits class of EdmondsKarp class. /// \param GR Digraph type. /// \param CAP Type of capacity map. template struct EdmondsKarpDefaultTraits { /// \brief The digraph type the algorithm runs on. typedef GR Digraph; /// \brief The type of the map that stores the arc capacities. /// /// The type of the map that stores the arc capacities. /// It must meet the \ref concepts::ReadMap "ReadMap" concept. typedef CAP CapacityMap; /// \brief The type of the length of the arcs. typedef typename CapacityMap::Value Value; /// \brief The map type that stores the flow values. /// /// The map type that stores the flow values. /// It must meet the \ref concepts::ReadWriteMap "ReadWriteMap" concept. typedef typename Digraph::template ArcMap FlowMap; /// \brief Instantiates a FlowMap. /// /// This function instantiates a \ref FlowMap. /// \param digraph The digraph, to which we would like to define the flow map. static FlowMap* createFlowMap(const Digraph& digraph) { return new FlowMap(digraph); } /// \brief The tolerance used by the algorithm /// /// The tolerance used by the algorithm to handle inexact computation. typedef lemon::Tolerance Tolerance; }; /// \ingroup max_flow /// /// \brief Edmonds-Karp algorithms class. /// /// This class provides an implementation of the \e Edmonds-Karp \e /// algorithm producing a flow of maximum value in directed /// digraphs. The Edmonds-Karp algorithm is slower than the Preflow /// algorithm but it has an advantage of the step-by-step execution /// control with feasible flow solutions. The \e source node, the \e /// target node, the \e capacity of the arcs and the \e starting \e /// flow value of the arcs should be passed to the algorithm /// through the constructor. /// /// The time complexity of the algorithm is \f$ O(nm^2) \f$ in /// worst case. Always try the preflow algorithm instead of this if /// you just want to compute the optimal flow. /// /// \param GR The digraph type the algorithm runs on. /// \param CAP The capacity map type. /// \param TR Traits class to set various data types used by /// the algorithm. The default traits class is \ref /// EdmondsKarpDefaultTraits. See \ref EdmondsKarpDefaultTraits for the /// documentation of a Edmonds-Karp traits class. #ifdef DOXYGEN template #else template , typename TR = EdmondsKarpDefaultTraits > #endif class EdmondsKarp { public: typedef TR Traits; typedef typename Traits::Digraph Digraph; typedef typename Traits::CapacityMap CapacityMap; typedef typename Traits::Value Value; typedef typename Traits::FlowMap FlowMap; typedef typename Traits::Tolerance Tolerance; private: TEMPLATE_DIGRAPH_TYPEDEFS(Digraph); typedef typename Digraph::template NodeMap PredMap; const Digraph& _graph; const CapacityMap* _capacity; Node _source, _target; FlowMap* _flow; bool _local_flow; PredMap* _pred; std::vector _queue; Tolerance _tolerance; Value _flow_value; void createStructures() { if (!_flow) { _flow = Traits::createFlowMap(_graph); _local_flow = true; } if (!_pred) { _pred = new PredMap(_graph); } _queue.resize(countNodes(_graph)); } void destroyStructures() { if (_local_flow) { delete _flow; } if (_pred) { delete _pred; } } public: ///\name Named template parameters ///@{ template struct DefFlowMapTraits : public Traits { typedef T FlowMap; static FlowMap *createFlowMap(const Digraph&) { LEMON_ASSERT(false,"Uninitialized parameter."); return 0; } }; /// \brief \ref named-templ-param "Named parameter" for setting /// FlowMap type /// /// \ref named-templ-param "Named parameter" for setting FlowMap /// type template struct DefFlowMap : public EdmondsKarp > { typedef EdmondsKarp > Create; }; /// @} protected: EdmondsKarp() {} public: /// \brief The constructor of the class. /// /// The constructor of the class. /// \param digraph The digraph the algorithm runs on. /// \param capacity The capacity of the arcs. /// \param source The source node. /// \param target The target node. EdmondsKarp(const Digraph& digraph, const CapacityMap& capacity, Node source, Node target) : _graph(digraph), _capacity(&capacity), _source(source), _target(target), _flow(0), _local_flow(false), _pred(0), _tolerance(), _flow_value() { LEMON_ASSERT(_source != _target,"Flow source and target are the same nodes."); } /// \brief Destructor. /// /// Destructor. ~EdmondsKarp() { destroyStructures(); } /// \brief Sets the capacity map. /// /// Sets the capacity map. /// \return \c (*this) EdmondsKarp& capacityMap(const CapacityMap& map) { _capacity = ↦ return *this; } /// \brief Sets the flow map. /// /// Sets the flow map. /// \return \c (*this) EdmondsKarp& flowMap(FlowMap& map) { if (_local_flow) { delete _flow; _local_flow = false; } _flow = ↦ return *this; } /// \brief Returns the flow map. /// /// \return The flow map. const FlowMap& flowMap() const { return *_flow; } /// \brief Sets the source node. /// /// Sets the source node. /// \return \c (*this) EdmondsKarp& source(const Node& node) { _source = node; return *this; } /// \brief Sets the target node. /// /// Sets the target node. /// \return \c (*this) EdmondsKarp& target(const Node& node) { _target = node; return *this; } /// \brief Sets the tolerance used by algorithm. /// /// Sets the tolerance used by algorithm. EdmondsKarp& tolerance(const Tolerance& tolerance) { _tolerance = tolerance; return *this; } /// \brief Returns the tolerance used by algorithm. /// /// Returns the tolerance used by algorithm. const Tolerance& tolerance() const { return _tolerance; } /// \name Execution control /// The simplest way to execute the /// algorithm is to use the \c run() member functions. /// \n /// If you need more control on initial solution or /// execution then you have to call one \ref init() function and then /// the start() or multiple times the \c augment() member function. ///@{ /// \brief Initializes the algorithm /// /// Sets the flow to empty flow. void init() { createStructures(); for (ArcIt it(_graph); it != INVALID; ++it) { _flow->set(it, 0); } _flow_value = 0; } /// \brief Initializes the algorithm /// /// Initializes the flow to the \c flowMap. The \c flowMap should /// contain a feasible flow, ie. in each node excluding the source /// and the target the incoming flow should be equal to the /// outgoing flow. template void flowInit(const FlowMap& flowMap) { createStructures(); for (ArcIt e(_graph); e != INVALID; ++e) { _flow->set(e, flowMap[e]); } _flow_value = 0; for (OutArcIt jt(_graph, _source); jt != INVALID; ++jt) { _flow_value += (*_flow)[jt]; } for (InArcIt jt(_graph, _source); jt != INVALID; ++jt) { _flow_value -= (*_flow)[jt]; } } /// \brief Initializes the algorithm /// /// Initializes the flow to the \c flowMap. The \c flowMap should /// contain a feasible flow, ie. in each node excluding the source /// and the target the incoming flow should be equal to the /// outgoing flow. /// \return %False when the given flowMap does not contain /// feasible flow. template bool checkedFlowInit(const FlowMap& flowMap) { createStructures(); for (ArcIt e(_graph); e != INVALID; ++e) { _flow->set(e, flowMap[e]); } for (NodeIt it(_graph); it != INVALID; ++it) { if (it == _source || it == _target) continue; Value outFlow = 0; for (OutArcIt jt(_graph, it); jt != INVALID; ++jt) { outFlow += (*_flow)[jt]; } Value inFlow = 0; for (InArcIt jt(_graph, it); jt != INVALID; ++jt) { inFlow += (*_flow)[jt]; } if (_tolerance.different(outFlow, inFlow)) { return false; } } for (ArcIt it(_graph); it != INVALID; ++it) { if (_tolerance.less((*_flow)[it], 0)) return false; if (_tolerance.less((*_capacity)[it], (*_flow)[it])) return false; } _flow_value = 0; for (OutArcIt jt(_graph, _source); jt != INVALID; ++jt) { _flow_value += (*_flow)[jt]; } for (InArcIt jt(_graph, _source); jt != INVALID; ++jt) { _flow_value -= (*_flow)[jt]; } return true; } /// \brief Augment the solution on an arc shortest path. /// /// Augment the solution on an arc shortest path. It searches an /// arc shortest path between the source and the target /// in the residual digraph by the bfs algoritm. /// Then it increases the flow on this path with the minimal residual /// capacity on the path. If there is no such path it gives back /// false. /// \return %False when the augmenting didn't success so the /// current flow is a feasible and optimal solution. bool augment() { for (NodeIt n(_graph); n != INVALID; ++n) { _pred->set(n, INVALID); } int first = 0, last = 1; _queue[0] = _source; _pred->set(_source, OutArcIt(_graph, _source)); while (first != last && (*_pred)[_target] == INVALID) { Node n = _queue[first++]; for (OutArcIt e(_graph, n); e != INVALID; ++e) { Value rem = (*_capacity)[e] - (*_flow)[e]; Node t = _graph.target(e); if (_tolerance.positive(rem) && (*_pred)[t] == INVALID) { _pred->set(t, e); _queue[last++] = t; } } for (InArcIt e(_graph, n); e != INVALID; ++e) { Value rem = (*_flow)[e]; Node t = _graph.source(e); if (_tolerance.positive(rem) && (*_pred)[t] == INVALID) { _pred->set(t, e); _queue[last++] = t; } } } if ((*_pred)[_target] != INVALID) { Node n = _target; Arc e = (*_pred)[n]; Value prem = (*_capacity)[e] - (*_flow)[e]; n = _graph.source(e); while (n != _source) { e = (*_pred)[n]; if (_graph.target(e) == n) { Value rem = (*_capacity)[e] - (*_flow)[e]; if (rem < prem) prem = rem; n = _graph.source(e); } else { Value rem = (*_flow)[e]; if (rem < prem) prem = rem; n = _graph.target(e); } } n = _target; e = (*_pred)[n]; _flow->set(e, (*_flow)[e] + prem); n = _graph.source(e); while (n != _source) { e = (*_pred)[n]; if (_graph.target(e) == n) { _flow->set(e, (*_flow)[e] + prem); n = _graph.source(e); } else { _flow->set(e, (*_flow)[e] - prem); n = _graph.target(e); } } _flow_value += prem; return true; } else { return false; } } /// \brief Executes the algorithm /// /// It runs augmenting phases until the optimal solution is reached. void start() { while (augment()) {} } /// \brief Runs the algorithm. /// /// It is just a shorthand for: /// ///\code /// ek.init(); /// ek.start(); ///\endcode void run() { init(); start(); } /// @} /// \name Query Functions /// The result of the Edmonds-Karp algorithm can be obtained using these /// functions.\n /// Before the use of these functions, /// either run() or start() must be called. ///@{ /// \brief Returns the value of the maximum flow. /// /// Returns the value of the maximum flow by returning the excess /// of the target node \c t. Value flowValue() const { return _flow_value; } /// \brief Returns the flow on the arc. /// /// Sets the \c flowMap to the flow on the arcs. Value flow(const Arc& arc) const { return (*_flow)[arc]; } /// \brief Returns true when the node is on the source side of minimum cut. /// /// Returns true when the node is on the source side of minimum /// cut. bool minCut(const Node& node) const { return ((*_pred)[node] != INVALID) or node == _source; } /// \brief Returns a minimum value cut. /// /// Sets \c cutMap to the characteristic vector of a minimum value cut. template void minCutMap(CutMap& cutMap) const { for (NodeIt n(_graph); n != INVALID; ++n) { cutMap.set(n, (*_pred)[n] != INVALID); } cutMap.set(_source, true); } /// @} }; } #endif