/* -*- C++ -*-

  *

  * This file is a part of LEMON, a generic C++ optimization library

  *

  * Copyright (C) 2003-2008

  * 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_SUURBALLE_H

 #define LEMON_SUURBALLE_H

 ///\ingroup shortest_path

 ///\file

 ///\brief An algorithm for finding edge-disjoint paths between two

 /// nodes having minimum total length.

 #include <vector>

 #include <lemon/bin_heap.h>

 #include <lemon/path.h>

 namespace lemon {

   /// \addtogroup shortest_path

   /// @{

   /// \brief Implementation of an algorithm for finding edge-disjoint

   /// paths between two nodes having minimum total length.

   ///

   /// \ref lemon::Suurballe "Suurballe" implements an algorithm for

   /// finding edge-disjoint paths having minimum total length (cost)

   /// from a given source node to a given target node in a directed

   /// graph.

   ///

   /// In fact, this implementation is the specialization of the

   /// \ref CapacityScaling "successive shortest path" algorithm.

   ///

   /// \tparam Graph The directed graph type the algorithm runs on.

   /// \tparam LengthMap The type of the length (cost) map.

   ///

   /// \warning Length values should be \e non-negative \e integers.

   ///

   /// \note For finding node-disjoint paths this algorithm can be used

   /// with \ref SplitGraphAdaptor.

   ///

   /// \author Attila Bernath and Peter Kovacs

   template < typename Graph, 

              typename LengthMap = typename Graph::template EdgeMap<int> >

   class Suurballe

   {

     GRAPH_TYPEDEFS(typename Graph);

     typedef typename LengthMap::Value Length;

     typedef ConstMap<Edge, int> ConstEdgeMap;

     typedef typename Graph::template NodeMap<Edge> PredMap;

   public:

     /// The type of the flow map.

     typedef typename Graph::template EdgeMap<int> FlowMap;

     /// The type of the potential map.

     typedef typename Graph::template NodeMap<Length> PotentialMap;

     /// The type of the path structures.

     typedef SimplePath<Graph> Path;

   private:

     /// \brief Special implementation of the \ref Dijkstra algorithm

     /// for finding shortest paths in the residual network.

     ///

     /// \ref ResidualDijkstra is a special implementation of the

     /// \ref Dijkstra algorithm for finding shortest paths in the

     /// residual network of the graph with respect to the reduced edge

     /// lengths and modifying the node potentials according to the

     /// distance of the nodes.

     class ResidualDijkstra

     {

       typedef typename Graph::template NodeMap<int> HeapCrossRef;

       typedef BinHeap<Length, HeapCrossRef> Heap;

     private:

       // The directed graph the algorithm runs on

       const Graph &_graph;

       // The main maps

       const FlowMap &_flow;

       const LengthMap &_length;

       PotentialMap &_potential;

       // The distance map

       PotentialMap _dist;

       // The pred edge map

       PredMap &_pred;

       // The processed (i.e. permanently labeled) nodes

       std::vector<Node> _proc_nodes;

       Node _s;

       Node _t;

     public:

       /// Constructor.

       ResidualDijkstra( const Graph &graph,

                         const FlowMap &flow,

                         const LengthMap &length,

                         PotentialMap &potential,

                         PredMap &pred,

                         Node s, Node t ) :

         _graph(graph), _flow(flow), _length(length), _potential(potential),

         _dist(graph), _pred(pred), _s(s), _t(t) {}

       /// \brief Runs the algorithm. Returns \c true if a path is found

       /// from the source node to the target node.

       bool run() {

         HeapCrossRef heap_cross_ref(_graph, Heap::PRE_HEAP);

         Heap heap(heap_cross_ref);

         heap.push(_s, 0);

         _pred[_s] = INVALID;

         _proc_nodes.clear();

         // Processing nodes

         while (!heap.empty() && heap.top() != _t) {

           Node u = heap.top(), v;

           Length d = heap.prio() + _potential[u], nd;

           _dist[u] = heap.prio();

           heap.pop();

           _proc_nodes.push_back(u);

           // Traversing outgoing edges

           for (OutEdgeIt e(_graph, u); e != INVALID; ++e) {

             if (_flow[e] == 0) {

               v = _graph.target(e);

               switch(heap.state(v)) {

               case Heap::PRE_HEAP:

                 heap.push(v, d + _length[e] - _potential[v]);

                 _pred[v] = e;

                 break;

               case Heap::IN_HEAP:

                 nd = d + _length[e] - _potential[v];

                 if (nd < heap[v]) {

                   heap.decrease(v, nd);

                   _pred[v] = e;

                 }

                 break;

               case Heap::POST_HEAP:

                 break;

               }

             }

           }

           // Traversing incoming edges

           for (InEdgeIt e(_graph, u); e != INVALID; ++e) {

             if (_flow[e] == 1) {

               v = _graph.source(e);

               switch(heap.state(v)) {

               case Heap::PRE_HEAP:

                 heap.push(v, d - _length[e] - _potential[v]);

                 _pred[v] = e;

                 break;

               case Heap::IN_HEAP:

                 nd = d - _length[e] - _potential[v];

                 if (nd < heap[v]) {

                   heap.decrease(v, nd);

                   _pred[v] = e;

                 }

                 break;

               case Heap::POST_HEAP:

                 break;

               }

             }

           }

         }

         if (heap.empty()) return false;

         // Updating potentials of processed nodes

         Length t_dist = heap.prio();

         for (int i = 0; i < int(_proc_nodes.size()); ++i)

           _potential[_proc_nodes[i]] += _dist[_proc_nodes[i]] - t_dist;

         return true;

       }

     }; //class ResidualDijkstra

   private:

     // The directed graph the algorithm runs on

     const Graph &_graph;

     // The length map

     const LengthMap &_length;

     // Edge map of the current flow

     FlowMap *_flow;

     bool _local_flow;

     // Node map of the current potentials

     PotentialMap *_potential;

     bool _local_potential;

     // The source node

     Node _source;

     // The target node

     Node _target;

     // Container to store the found paths

     std::vector< SimplePath<Graph> > paths;

     int _path_num;

     // The pred edge map

     PredMap _pred;

     // Implementation of the Dijkstra algorithm for finding augmenting

     // shortest paths in the residual network

     ResidualDijkstra *_dijkstra;

   public:

     /// \brief Constructor.

     ///

     /// Constructor.

     ///

     /// \param graph The directed graph the algorithm runs on.

     /// \param length The length (cost) values of the edges.

     /// \param s The source node.

     /// \param t The target node.

     Suurballe( const Graph &graph,

                const LengthMap &length,

                Node s, Node t ) :

       _graph(graph), _length(length), _flow(0), _local_flow(false),

       _potential(0), _local_potential(false), _source(s), _target(t),

       _pred(graph) {}

     /// Destructor.

     ~Suurballe() {

       if (_local_flow) delete _flow;

       if (_local_potential) delete _potential;

       delete _dijkstra;

     }

     /// \brief Sets the flow map.

     ///

     /// Sets the flow map.

     ///

     /// The found flow contains only 0 and 1 values. It is the union of

     /// the found edge-disjoint paths.

     ///

     /// \return \c (*this)

     Suurballe& flowMap(FlowMap &map) {

       if (_local_flow) {

         delete _flow;

         _local_flow = false;

       }

       _flow = ↦

       return *this;

     }

     /// \brief Sets the potential map.

     ///

     /// Sets the potential map.

     ///

     /// The potentials provide the dual solution of the underlying 

     /// minimum cost flow problem.

     ///

     /// \return \c (*this)

     Suurballe& potentialMap(PotentialMap &map) {

       if (_local_potential) {

         delete _potential;

         _local_potential = false;

       }

       _potential = ↦

       return *this;

     }

     /// \name Execution control

     /// The simplest way to execute the algorithm is to call the run()

     /// function.

     /// \n

     /// If you only need the flow that is the union of the found

     /// edge-disjoint paths, you may call init() and findFlow().

     /// @{

     /// \brief Runs the algorithm.

     ///

     /// Runs the algorithm.

     ///

     /// \param k The number of paths to be found.

     ///

     /// \return \c k if there are at least \c k edge-disjoint paths

     /// from \c s to \c t. Otherwise it returns the number of

     /// edge-disjoint paths found.

     ///

     /// \note Apart from the return value, <tt>s.run(k)</tt> is just a

     /// shortcut of the following code.

     /// \code

     ///   s.init();

     ///   s.findFlow(k);

     ///   s.findPaths();

     /// \endcode

     int run(int k = 2) {

       init();

       findFlow(k);

       findPaths();

       return _path_num;

     }

     /// \brief Initializes the algorithm.

     ///

     /// Initializes the algorithm.

     void init() {

       // Initializing maps

       if (!_flow) {

         _flow = new FlowMap(_graph);

         _local_flow = true;

       }

       if (!_potential) {

         _potential = new PotentialMap(_graph);

         _local_potential = true;

       }

       for (EdgeIt e(_graph); e != INVALID; ++e) (*_flow)[e] = 0;

       for (NodeIt n(_graph); n != INVALID; ++n) (*_potential)[n] = 0;

       _dijkstra = new ResidualDijkstra( _graph, *_flow, _length, 

                                         *_potential, _pred,

                                         _source, _target );

     }

     /// \brief Executes the successive shortest path algorithm to find

     /// an optimal flow.

     ///

     /// Executes the successive shortest path algorithm to find a

     /// minimum cost flow, which is the union of \c k or less

     /// edge-disjoint paths.

     ///

     /// \return \c k if there are at least \c k edge-disjoint paths

     /// from \c s to \c t. Otherwise it returns the number of

     /// edge-disjoint paths found.

     ///

     /// \pre \ref init() must be called before using this function.

     int findFlow(int k = 2) {

       // Finding shortest paths

       _path_num = 0;

       while (_path_num < k) {

         // Running Dijkstra

         if (!_dijkstra->run()) break;

         ++_path_num;

         // Setting the flow along the found shortest path

         Node u = _target;

         Edge e;

         while ((e = _pred[u]) != INVALID) {

           if (u == _graph.target(e)) {

             (*_flow)[e] = 1;

             u = _graph.source(e);

           } else {

             (*_flow)[e] = 0;

             u = _graph.target(e);

           }

         }

       }

       return _path_num;

     }

     /// \brief Computes the paths from the flow.

     ///

     /// Computes the paths from the flow.

     ///

     /// \pre \ref init() and \ref findFlow() must be called before using

     /// this function.

     void findPaths() {

       // Creating the residual flow map (the union of the paths not

       // found so far)

       FlowMap res_flow(*_flow);

       paths.clear();

       paths.resize(_path_num);

       for (int i = 0; i < _path_num; ++i) {

         Node n = _source;

         while (n != _target) {

           OutEdgeIt e(_graph, n);

           for ( ; res_flow[e] == 0; ++e) ;

           n = _graph.target(e);

           paths[i].addBack(e);

           res_flow[e] = 0;

         }

       }

     }

     /// @}

     /// \name Query Functions

     /// The result of the algorithm can be obtained using these

     /// functions.

     /// \n The algorithm should be executed before using them.

     /// @{

     /// \brief Returns a const reference to the edge map storing the

     /// found flow.

     ///

     /// Returns a const reference to the edge map storing the flow that

     /// is the union of the found edge-disjoint paths.

     ///

     /// \pre \ref run() or findFlow() must be called before using this

     /// function.

     const FlowMap& flowMap() const {

       return *_flow;

     }

     /// \brief Returns a const reference to the node map storing the

     /// found potentials (the dual solution).

     ///

     /// Returns a const reference to the node map storing the found

     /// potentials that provide the dual solution of the underlying 

     /// minimum cost flow problem.

     ///

     /// \pre \ref run() or findFlow() must be called before using this

     /// function.

     const PotentialMap& potentialMap() const {

       return *_potential;

     }

     /// \brief Returns the flow on the given edge.

     ///

     /// Returns the flow on the given edge.

     /// It is \c 1 if the edge is involved in one of the found paths,

     /// otherwise it is \c 0.

     ///

     /// \pre \ref run() or findFlow() must be called before using this

     /// function.

     int flow(const Edge& edge) const {

       return (*_flow)[edge];

     }

     /// \brief Returns the potential of the given node.

     ///

     /// Returns the potential of the given node.

     ///

     /// \pre \ref run() or findFlow() must be called before using this

     /// function.

     Length potential(const Node& node) const {

       return (*_potential)[node];

     }

     /// \brief Returns the total length (cost) of the found paths (flow).

     ///

     /// Returns the total length (cost) of the found paths (flow).

     /// The complexity of the function is \f$ O(e) \f$.

     ///

     /// \pre \ref run() or findFlow() must be called before using this

     /// function.

     Length totalLength() const {

       Length c = 0;

       for (EdgeIt e(_graph); e != INVALID; ++e)

         c += (*_flow)[e] * _length[e];

       return c;

     }

     /// \brief Returns the number of the found paths.

     ///

     /// Returns the number of the found paths.

     ///

     /// \pre \ref run() or findFlow() must be called before using this

     /// function.

     int pathNum() const {

       return _path_num;

     }

     /// \brief Returns a const reference to the specified path.

     ///

     /// Returns a const reference to the specified path.

     ///

     /// \param i The function returns the \c i-th path.

     /// \c i must be between \c 0 and <tt>%pathNum()-1</tt>.

     ///

     /// \pre \ref run() or findPaths() must be called before using this

     /// function.

     Path path(int i) const {

       return paths[i];

     }

     /// @}

   }; //class Suurballe

   ///@}

 } //namespace lemon

 #endif //LEMON_SUURBALLE_H