src/work/jacint/max_flow.h
author marci
Fri, 14 May 2004 15:19:18 +0000
changeset 639 a11a4377a816
parent 631 26819ef1611f
child 640 d426dca0aaf7
permissions -rw-r--r--
misc
     1 // -*- C++ -*-
     2 #ifndef HUGO_MAX_FLOW_H
     3 #define HUGO_MAX_FLOW_H
     4 
     5 #include <vector>
     6 #include <queue>
     7 #include <stack>
     8 
     9 #include <hugo/graph_wrapper.h>
    10 #include <bfs_dfs.h>
    11 #include <hugo/invalid.h>
    12 #include <hugo/maps.h>
    13 #include <for_each_macros.h>
    14 
    15 /// \file
    16 /// \brief Maximum flow algorithms.
    17 /// \ingroup galgs
    18 
    19 namespace hugo {
    20 
    21   /// \addtogroup galgs
    22   /// @{                                                                                                                                        
    23   ///Maximum flow algorithms class.
    24 
    25   ///This class provides various algorithms for finding a flow of
    26   ///maximum value in a directed graph. The \e source node, the \e
    27   ///target node, the \e capacity of the edges and the \e starting \e
    28   ///flow value of the edges can be passed to the algorithm through the
    29   ///constructor. It is possible to change these quantities using the
    30   ///functions \ref resetSource, \ref resetTarget, \ref resetCap and
    31   ///\ref resetFlow. Before any subsequent runs of any algorithm of
    32   ///the class \ref resetFlow should be called, otherwise it will
    33   ///start from a maximum flow.                                                                                                                 
    34   ///After running an algorithm of the class, the maximum value of a
    35   ///value can be obtained by calling \ref flowValue(). The minimum
    36   ///value cut can be written into a \c node map of \c bools by
    37   ///calling \ref minCut. (\ref minMinCut and \ref maxMinCut writes
    38   ///the inclusionwise minimum and maximum of the minimum value
    39   ///cuts, resp.)                                                                                                                               
    40   ///\param Graph The directed graph type the algorithm runs on.
    41   ///\param Num The number type of the capacities and the flow values.
    42   ///\param CapMap The type of the capacity map.
    43   ///\param FlowMap The type of the flow map.                                                                                                           
    44   ///\author Marton Makai, Jacint Szabo 
    45   template <typename Graph, typename Num,
    46 	    typename CapMap=typename Graph::template EdgeMap<Num>,
    47             typename FlowMap=typename Graph::template EdgeMap<Num> >
    48   class MaxFlow {
    49   protected:
    50     typedef typename Graph::Node Node;
    51     typedef typename Graph::NodeIt NodeIt;
    52     typedef typename Graph::EdgeIt EdgeIt;
    53     typedef typename Graph::OutEdgeIt OutEdgeIt;
    54     typedef typename Graph::InEdgeIt InEdgeIt;
    55 
    56     typedef typename std::vector<std::stack<Node> > VecStack;
    57     typedef typename Graph::template NodeMap<Node> NNMap;
    58     typedef typename std::vector<Node> VecNode;
    59 
    60     const Graph* g;
    61     Node s;
    62     Node t;
    63     const CapMap* capacity;
    64     FlowMap* flow;
    65     int n;      //the number of nodes of G
    66     typedef ResGraphWrapper<const Graph, Num, CapMap, FlowMap> ResGW;
    67     typedef typename ResGW::OutEdgeIt ResGWOutEdgeIt;
    68     typedef typename ResGW::Edge ResGWEdge;
    69     //typedef typename ResGW::template NodeMap<bool> ReachedMap;
    70     typedef typename Graph::template NodeMap<int> ReachedMap;
    71 
    72 
    73     //level works as a bool map in augmenting path algorithms and is
    74     //used by bfs for storing reached information.  In preflow, it
    75     //shows the levels of nodes.     
    76     ReachedMap level;
    77 
    78     //excess is needed only in preflow
    79     typename Graph::template NodeMap<Num> excess;
    80 
    81     //fixme    
    82 //   protected:
    83     //     MaxFlow() { }
    84     //     void set(const Graph& _G, Node _s, Node _t, const CapMap& _capacity,
    85     // 	     FlowMap& _flow)
    86     //       {
    87     // 	g=&_G;
    88     // 	s=_s;
    89     // 	t=_t;
    90     // 	capacity=&_capacity;
    91     // 	flow=&_flow;
    92     // 	n=_G.nodeNum;
    93     // 	level.set (_G); //kellene vmi ilyesmi fv
    94     // 	excess(_G,0); //itt is
    95     //       }
    96 
    97     // constants used for heuristics
    98     static const int H0=20;
    99     static const int H1=1;
   100 
   101   public:
   102 
   103     ///Indicates the property of the starting flow.
   104 
   105     ///Indicates the property of the starting flow. The meanings are as follows:
   106     ///- \c ZERO_FLOW: constant zero flow
   107     ///- \c GEN_FLOW: any flow, i.e. the sum of the in-flows equals to
   108     ///the sum of the out-flows in every node except the \e source and
   109     ///the \e target.
   110     ///- \c PRE_FLOW: any preflow, i.e. the sum of the in-flows is at 
   111     ///least the sum of the out-flows in every node except the \e source.
   112     ///- \c NO_FLOW: indicates an unspecified edge map. \ref flow will be 
   113     ///set to the constant zero flow in the beginning of the algorithm in this case.
   114     enum flowEnum{
   115       ZERO_FLOW,
   116       GEN_FLOW,
   117       PRE_FLOW,
   118       NO_FLOW
   119     };
   120 
   121     MaxFlow(const Graph& _G, Node _s, Node _t, const CapMap& _capacity,
   122 	    FlowMap& _flow) :
   123       g(&_G), s(_s), t(_t), capacity(&_capacity),
   124       flow(&_flow), n(_G.nodeNum()), level(_G), excess(_G,0) {}
   125 
   126     ///Runs a maximum flow algorithm.
   127 
   128     ///Runs a preflow algorithm, which is the fastest maximum flow
   129     ///algorithm up-to-date. The default for \c fe is ZERO_FLOW.
   130     ///\pre The starting flow must be
   131     /// - a constant zero flow if \c fe is \c ZERO_FLOW,
   132     /// - an arbitary flow if \c fe is \c GEN_FLOW,
   133     /// - an arbitary preflow if \c fe is \c PRE_FLOW,
   134     /// - any map if \c fe is NO_FLOW.
   135     void run(flowEnum fe=ZERO_FLOW) {
   136       preflow(fe);
   137     }
   138 
   139                                                                                              
   140     ///Runs a preflow algorithm.  
   141 
   142     ///Runs a preflow algorithm. The preflow algorithms provide the
   143     ///fastest way to compute a maximum flow in a directed graph.
   144     ///\pre The starting flow must be
   145     /// - a constant zero flow if \c fe is \c ZERO_FLOW,
   146     /// - an arbitary flow if \c fe is \c GEN_FLOW,
   147     /// - an arbitary preflow if \c fe is \c PRE_FLOW,
   148     /// - any map if \c fe is NO_FLOW.
   149     void preflow(flowEnum fe) {
   150       preflowPhase1(fe);
   151       preflowPhase2();
   152     }
   153     // Heuristics:
   154     //   2 phase
   155     //   gap
   156     //   list 'level_list' on the nodes on level i implemented by hand
   157     //   stack 'active' on the active nodes on level i                                                                                    
   158     //   runs heuristic 'highest label' for H1*n relabels
   159     //   runs heuristic 'bound decrease' for H0*n relabels, starts with 'highest label'
   160     //   Parameters H0 and H1 are initialized to 20 and 1.
   161 
   162     ///Runs the first phase of the preflow algorithm.
   163 
   164     ///The preflow algorithm consists of two phases, this method runs the
   165     ///first phase. After the first phase the maximum flow value and a
   166     ///minimum value cut can already be computed, though a maximum flow
   167     ///is net yet obtained. So after calling this method \ref flowValue
   168     ///and \ref actMinCut gives proper results.
   169     ///\warning: \ref minCut, \ref minMinCut and \ref maxMinCut do not
   170     ///give minimum value cuts unless calling \ref preflowPhase2.
   171     ///\pre The starting flow must be
   172     /// - a constant zero flow if \c fe is \c ZERO_FLOW,
   173     /// - an arbitary flow if \c fe is \c GEN_FLOW,
   174     /// - an arbitary preflow if \c fe is \c PRE_FLOW,
   175     /// - any map if \c fe is NO_FLOW.
   176     void preflowPhase1( flowEnum fe );
   177 
   178     ///Runs the second phase of the preflow algorithm.
   179 
   180     ///The preflow algorithm consists of two phases, this method runs
   181     ///the second phase. After calling \ref preflowPhase1 and then
   182     ///\ref preflowPhase2 the methods \ref flowValue, \ref minCut,
   183     ///\ref minMinCut and \ref maxMinCut give proper results.
   184     ///\pre \ref preflowPhase1 must be called before.
   185     void preflowPhase2();
   186 
   187     /// Starting from a flow, this method searches for an augmenting path
   188     /// according to the Edmonds-Karp algorithm
   189     /// and augments the flow on if any.
   190     /// The return value shows if the augmentation was succesful.
   191     bool augmentOnShortestPath();
   192 
   193     /// Starting from a flow, this method searches for an augmenting blocking
   194     /// flow according to Dinits' algorithm and augments the flow on if any.
   195     /// The blocking flow is computed in a physically constructed
   196     /// residual graph of type \c Mutablegraph.
   197     /// The return value show sif the augmentation was succesful.
   198     template<typename MutableGraph> bool augmentOnBlockingFlow();
   199 
   200     /// The same as \c augmentOnBlockingFlow<MutableGraph> but the
   201     /// residual graph is not constructed physically.
   202     /// The return value shows if the augmentation was succesful.
   203     bool augmentOnBlockingFlow2();
   204 
   205     /// Returns the maximum value of a flow.
   206 
   207     /// Returns the maximum value of a flow, by counting the 
   208     /// over-flow of the target node \ref t.
   209     /// It can be called already after running \ref preflowPhase1.
   210     Num flowValue() {
   211       Num a=0;
   212       FOR_EACH_INC_LOC(InEdgeIt, e, *g, t) a+=(*flow)[e];
   213       FOR_EACH_INC_LOC(OutEdgeIt, e, *g, t) a-=(*flow)[e];
   214       return a;
   215       //marci figyu: excess[t] epp ezt adja preflow 1. fazisa utan   
   216     }
   217 
   218     ///Returns a minimum value cut after calling \ref preflowPhase1.
   219 
   220     ///After the first phase of the preflow algorithm the maximum flow
   221     ///value and a minimum value cut can already be computed. This
   222     ///method can be called after running \ref preflowPhase1 for
   223     ///obtaining a minimum value cut.
   224     /// \warning Gives proper result only right after calling \ref
   225     /// preflowPhase1.
   226     /// \todo We have to make some status variable which shows the
   227     /// actual state
   228     /// of the class. This enables us to determine which methods are valid
   229     /// for MinCut computation
   230     template<typename _CutMap>
   231     void actMinCut(_CutMap& M) {
   232       NodeIt v;
   233       for(g->first(v); g->valid(v); g->next(v)) {
   234 	if ( level[v] < n ) {
   235 	  M.set(v,false);
   236 	} else {
   237 	  M.set(v,true);
   238 	}
   239       }
   240     }
   241 
   242     ///Returns the inclusionwise minimum of the minimum value cuts.
   243 
   244     ///Sets \c M to the characteristic vector of the minimum value cut
   245     ///which is inclusionwise minimum. It is computed by processing
   246     ///a bfs from the source node \c s in the residual graph.
   247     ///\pre M should be a node map of bools initialized to false.
   248     ///\pre \c flow must be a maximum flow.
   249     template<typename _CutMap>
   250     void minMinCut(_CutMap& M) {
   251 
   252       std::queue<Node> queue;
   253 
   254       M.set(s,true);
   255       queue.push(s);
   256 
   257       while (!queue.empty()) {
   258         Node w=queue.front();
   259 	queue.pop();
   260 
   261 	OutEdgeIt e;
   262 	for(g->first(e,w) ; g->valid(e); g->next(e)) {
   263 	  Node v=g->head(e);
   264 	  if (!M[v] && (*flow)[e] < (*capacity)[e] ) {
   265 	    queue.push(v);
   266 	    M.set(v, true);
   267 	  }
   268 	}
   269 
   270 	InEdgeIt f;
   271 	for(g->first(f,w) ; g->valid(f); g->next(f)) {
   272 	  Node v=g->tail(f);
   273 	  if (!M[v] && (*flow)[f] > 0 ) {
   274 	    queue.push(v);
   275 	    M.set(v, true);
   276 	  }
   277 	}
   278       }
   279     }
   280 
   281     ///Returns the inclusionwise maximum of the minimum value cuts.
   282 
   283     ///Sets \c M to the characteristic vector of the minimum value cut
   284     ///which is inclusionwise maximum. It is computed by processing a
   285     ///backward bfs from the target node \c t in the residual graph.
   286     ///\pre M should be a node map of bools initialized to false.
   287     ///\pre \c flow must be a maximum flow. 
   288     template<typename _CutMap>
   289     void maxMinCut(_CutMap& M) {
   290 
   291       NodeIt v;
   292       for(g->first(v) ; g->valid(v); g->next(v)) {
   293 	M.set(v, true);
   294       }
   295 
   296       std::queue<Node> queue;
   297 
   298       M.set(t,false);
   299       queue.push(t);
   300 
   301       while (!queue.empty()) {
   302         Node w=queue.front();
   303 	queue.pop();
   304 
   305 	InEdgeIt e;
   306 	for(g->first(e,w) ; g->valid(e); g->next(e)) {
   307 	  Node v=g->tail(e);
   308 	  if (M[v] && (*flow)[e] < (*capacity)[e] ) {
   309 	    queue.push(v);
   310 	    M.set(v, false);
   311 	  }
   312 	}
   313 
   314 	OutEdgeIt f;
   315 	for(g->first(f,w) ; g->valid(f); g->next(f)) {
   316 	  Node v=g->head(f);
   317 	  if (M[v] && (*flow)[f] > 0 ) {
   318 	    queue.push(v);
   319 	    M.set(v, false);
   320 	  }
   321 	}
   322       }
   323     }
   324 
   325     ///Returns a minimum value cut.
   326 
   327     ///Sets \c M to the characteristic vector of a minimum value cut.
   328     ///\pre M should be a node map of bools initialized to false.
   329     ///\pre \c flow must be a maximum flow.    
   330     template<typename CutMap>
   331     void minCut(CutMap& M) { minMinCut(M); }
   332 
   333     ///Resets the source node to \c _s.
   334 
   335     ///Resets the source node to \c _s.
   336     /// 
   337     void resetSource(Node _s) { s=_s; }
   338 
   339     ///Resets the target node to \c _t.
   340 
   341     ///Resets the target node to \c _t.
   342     ///
   343     void resetTarget(Node _t) { t=_t; }
   344 
   345     /// Resets the edge map of the capacities to _cap.
   346 
   347     /// Resets the edge map of the capacities to _cap.
   348     /// 
   349     void resetCap(const CapMap& _cap) { capacity=&_cap; }
   350 
   351     /// Resets the edge map of the flows to _flow.
   352 
   353     /// Resets the edge map of the flows to _flow.
   354     /// 
   355     void resetFlow(FlowMap& _flow) { flow=&_flow; }
   356 
   357 
   358   private:
   359 
   360     int push(Node w, VecStack& active) {
   361 
   362       int lev=level[w];
   363       Num exc=excess[w];
   364       int newlevel=n;       //bound on the next level of w
   365 
   366       OutEdgeIt e;
   367       for(g->first(e,w); g->valid(e); g->next(e)) {
   368 
   369 	if ( (*flow)[e] >= (*capacity)[e] ) continue;
   370 	Node v=g->head(e);
   371 
   372 	if( lev > level[v] ) { //Push is allowed now
   373 
   374 	  if ( excess[v]<=0 && v!=t && v!=s ) {
   375 	    int lev_v=level[v];
   376 	    active[lev_v].push(v);
   377 	  }
   378 
   379 	  Num cap=(*capacity)[e];
   380 	  Num flo=(*flow)[e];
   381 	  Num remcap=cap-flo;
   382 
   383 	  if ( remcap >= exc ) { //A nonsaturating push.
   384 
   385 	    flow->set(e, flo+exc);
   386 	    excess.set(v, excess[v]+exc);
   387 	    exc=0;
   388 	    break;
   389 
   390 	  } else { //A saturating push.
   391 	    flow->set(e, cap);
   392 	    excess.set(v, excess[v]+remcap);
   393 	    exc-=remcap;
   394 	  }
   395 	} else if ( newlevel > level[v] ) newlevel = level[v];
   396       } //for out edges wv
   397 
   398       if ( exc > 0 ) {
   399 	InEdgeIt e;
   400 	for(g->first(e,w); g->valid(e); g->next(e)) {
   401 
   402 	  if( (*flow)[e] <= 0 ) continue;
   403 	  Node v=g->tail(e);
   404 
   405 	  if( lev > level[v] ) { //Push is allowed now
   406 
   407 	    if ( excess[v]<=0 && v!=t && v!=s ) {
   408 	      int lev_v=level[v];
   409 	      active[lev_v].push(v);
   410 	    }
   411 
   412 	    Num flo=(*flow)[e];
   413 
   414 	    if ( flo >= exc ) { //A nonsaturating push.
   415 
   416 	      flow->set(e, flo-exc);
   417 	      excess.set(v, excess[v]+exc);
   418 	      exc=0;
   419 	      break;
   420 	    } else {  //A saturating push.
   421 
   422 	      excess.set(v, excess[v]+flo);
   423 	      exc-=flo;
   424 	      flow->set(e,0);
   425 	    }
   426 	  } else if ( newlevel > level[v] ) newlevel = level[v];
   427 	} //for in edges vw
   428 
   429       } // if w still has excess after the out edge for cycle
   430 
   431       excess.set(w, exc);
   432 
   433       return newlevel;
   434     }
   435 
   436 
   437     void preflowPreproc(flowEnum fe, VecStack& active,
   438 			VecNode& level_list, NNMap& left, NNMap& right)
   439     {
   440       std::queue<Node> bfs_queue;
   441 
   442       switch (fe) {
   443       case NO_FLOW:   //flow is already set to const zero in this case
   444       case ZERO_FLOW:
   445 	{
   446 	  //Reverse_bfs from t, to find the starting level.
   447 	  level.set(t,0);
   448 	  bfs_queue.push(t);
   449 
   450 	  while (!bfs_queue.empty()) {
   451 
   452 	    Node v=bfs_queue.front();
   453 	    bfs_queue.pop();
   454 	    int l=level[v]+1;
   455 
   456 	    InEdgeIt e;
   457 	    for(g->first(e,v); g->valid(e); g->next(e)) {
   458 	      Node w=g->tail(e);
   459 	      if ( level[w] == n && w != s ) {
   460 		bfs_queue.push(w);
   461 		Node first=level_list[l];
   462 		if ( g->valid(first) ) left.set(first,w);
   463 		right.set(w,first);
   464 		level_list[l]=w;
   465 		level.set(w, l);
   466 	      }
   467 	    }
   468 	  }
   469 
   470 	  //the starting flow
   471 	  OutEdgeIt e;
   472 	  for(g->first(e,s); g->valid(e); g->next(e))
   473 	    {
   474 	      Num c=(*capacity)[e];
   475 	      if ( c <= 0 ) continue;
   476 	      Node w=g->head(e);
   477 	      if ( level[w] < n ) {
   478 		if ( excess[w] <= 0 && w!=t ) active[level[w]].push(w);
   479 		flow->set(e, c);
   480 		excess.set(w, excess[w]+c);
   481 	      }
   482 	    }
   483 	  break;
   484 	}
   485 
   486       case GEN_FLOW:
   487       case PRE_FLOW:
   488 	{
   489 	  //Reverse_bfs from t in the residual graph,
   490 	  //to find the starting level.
   491 	  level.set(t,0);
   492 	  bfs_queue.push(t);
   493 
   494 	  while (!bfs_queue.empty()) {
   495 
   496 	    Node v=bfs_queue.front();
   497 	    bfs_queue.pop();
   498 	    int l=level[v]+1;
   499 
   500 	    InEdgeIt e;
   501 	    for(g->first(e,v); g->valid(e); g->next(e)) {
   502 	      if ( (*capacity)[e] <= (*flow)[e] ) continue;
   503 	      Node w=g->tail(e);
   504 	      if ( level[w] == n && w != s ) {
   505 		bfs_queue.push(w);
   506 		Node first=level_list[l];
   507 		if ( g->valid(first) ) left.set(first,w);
   508 		right.set(w,first);
   509 		level_list[l]=w;
   510 		level.set(w, l);
   511 	      }
   512 	    }
   513 
   514 	    OutEdgeIt f;
   515 	    for(g->first(f,v); g->valid(f); g->next(f)) {
   516 	      if ( 0 >= (*flow)[f] ) continue;
   517 	      Node w=g->head(f);
   518 	      if ( level[w] == n && w != s ) {
   519 		bfs_queue.push(w);
   520 		Node first=level_list[l];
   521 		if ( g->valid(first) ) left.set(first,w);
   522 		right.set(w,first);
   523 		level_list[l]=w;
   524 		level.set(w, l);
   525 	      }
   526 	    }
   527 	  }
   528 
   529 
   530 	  //the starting flow
   531 	  OutEdgeIt e;
   532 	  for(g->first(e,s); g->valid(e); g->next(e))
   533 	    {
   534 	      Num rem=(*capacity)[e]-(*flow)[e];
   535 	      if ( rem <= 0 ) continue;
   536 	      Node w=g->head(e);
   537 	      if ( level[w] < n ) {
   538 		if ( excess[w] <= 0 && w!=t ) active[level[w]].push(w);
   539 		flow->set(e, (*capacity)[e]);
   540 		excess.set(w, excess[w]+rem);
   541 	      }
   542 	    }
   543 
   544 	  InEdgeIt f;
   545 	  for(g->first(f,s); g->valid(f); g->next(f))
   546 	    {
   547 	      if ( (*flow)[f] <= 0 ) continue;
   548 	      Node w=g->tail(f);
   549 	      if ( level[w] < n ) {
   550 		if ( excess[w] <= 0 && w!=t ) active[level[w]].push(w);
   551 		excess.set(w, excess[w]+(*flow)[f]);
   552 		flow->set(f, 0);
   553 	      }
   554 	    }
   555 	  break;
   556 	} //case PRE_FLOW
   557       }
   558     } //preflowPreproc
   559 
   560 
   561 
   562     void relabel(Node w, int newlevel, VecStack& active,
   563 		 VecNode& level_list, NNMap& left,
   564 		 NNMap& right, int& b, int& k, bool what_heur )
   565     {
   566 
   567       Num lev=level[w];
   568 
   569       Node right_n=right[w];
   570       Node left_n=left[w];
   571 
   572       //unlacing starts
   573       if ( g->valid(right_n) ) {
   574 	if ( g->valid(left_n) ) {
   575 	  right.set(left_n, right_n);
   576 	  left.set(right_n, left_n);
   577 	} else {
   578 	  level_list[lev]=right_n;
   579 	  left.set(right_n, INVALID);
   580 	}
   581       } else {
   582 	if ( g->valid(left_n) ) {
   583 	  right.set(left_n, INVALID);
   584 	} else {
   585 	  level_list[lev]=INVALID;
   586 	}
   587       }
   588       //unlacing ends
   589 
   590       if ( !g->valid(level_list[lev]) ) {
   591 
   592 	//gapping starts
   593 	for (int i=lev; i!=k ; ) {
   594 	  Node v=level_list[++i];
   595 	  while ( g->valid(v) ) {
   596 	    level.set(v,n);
   597 	    v=right[v];
   598 	  }
   599 	  level_list[i]=INVALID;
   600 	  if ( !what_heur ) {
   601 	    while ( !active[i].empty() ) {
   602 	      active[i].pop();    //FIXME: ezt szebben kene
   603 	    }
   604 	  }
   605 	}
   606 
   607 	level.set(w,n);
   608 	b=lev-1;
   609 	k=b;
   610 	//gapping ends
   611 
   612       } else {
   613 
   614 	if ( newlevel == n ) level.set(w,n);
   615 	else {
   616 	  level.set(w,++newlevel);
   617 	  active[newlevel].push(w);
   618 	  if ( what_heur ) b=newlevel;
   619 	  if ( k < newlevel ) ++k;      //now k=newlevel
   620 	  Node first=level_list[newlevel];
   621 	  if ( g->valid(first) ) left.set(first,w);
   622 	  right.set(w,first);
   623 	  left.set(w,INVALID);
   624 	  level_list[newlevel]=w;
   625 	}
   626       }
   627 
   628     } //relabel
   629 
   630 
   631     template<typename MapGraphWrapper>
   632     class DistanceMap {
   633     protected:
   634       const MapGraphWrapper* g;
   635       typename MapGraphWrapper::template NodeMap<int> dist;
   636     public:
   637       DistanceMap(MapGraphWrapper& _g) : g(&_g), dist(*g, g->nodeNum()) { }
   638       void set(const typename MapGraphWrapper::Node& n, int a) {
   639 	dist.set(n, a);
   640       }
   641       int operator[](const typename MapGraphWrapper::Node& n)
   642       { return dist[n]; }
   643       //       int get(const typename MapGraphWrapper::Node& n) const {
   644       // 	return dist[n]; }
   645       //       bool get(const typename MapGraphWrapper::Edge& e) const {
   646       // 	return (dist.get(g->tail(e))<dist.get(g->head(e))); }
   647       bool operator[](const typename MapGraphWrapper::Edge& e) const {
   648 	return (dist[g->tail(e)]<dist[g->head(e)]);
   649       }
   650     };
   651 
   652   };
   653 
   654 
   655   template <typename Graph, typename Num, typename CapMap, typename FlowMap>
   656   void MaxFlow<Graph, Num, CapMap, FlowMap>::preflowPhase1( flowEnum fe )
   657   {
   658 
   659     int heur0=(int)(H0*n);  //time while running 'bound decrease'
   660     int heur1=(int)(H1*n);  //time while running 'highest label'
   661     int heur=heur1;         //starting time interval (#of relabels)
   662     int numrelabel=0;
   663 
   664     bool what_heur=1;
   665     //It is 0 in case 'bound decrease' and 1 in case 'highest label'
   666 
   667     bool end=false;
   668     //Needed for 'bound decrease', true means no active nodes are above bound
   669     //b.
   670 
   671     int k=n-2;  //bound on the highest level under n containing a node
   672     int b=k;    //bound on the highest level under n of an active node
   673 
   674     VecStack active(n);
   675 
   676     NNMap left(*g, INVALID);
   677     NNMap right(*g, INVALID);
   678     VecNode level_list(n,INVALID);
   679     //List of the nodes in level i<n, set to n.
   680 
   681     NodeIt v;
   682     for(g->first(v); g->valid(v); g->next(v)) level.set(v,n);
   683     //setting each node to level n
   684 
   685     if ( fe == NO_FLOW ) {
   686       EdgeIt e;
   687       for(g->first(e); g->valid(e); g->next(e)) flow->set(e,0);
   688     }
   689 
   690     switch (fe) { //computing the excess
   691     case PRE_FLOW:
   692       {
   693 	NodeIt v;
   694 	for(g->first(v); g->valid(v); g->next(v)) {
   695 	  Num exc=0;
   696 
   697 	  InEdgeIt e;
   698 	  for(g->first(e,v); g->valid(e); g->next(e)) exc+=(*flow)[e];
   699 	  OutEdgeIt f;
   700 	  for(g->first(f,v); g->valid(f); g->next(f)) exc-=(*flow)[f];
   701 
   702 	  excess.set(v,exc);
   703 
   704 	  //putting the active nodes into the stack
   705 	  int lev=level[v];
   706 	  if ( exc > 0 && lev < n && v != t ) active[lev].push(v);
   707 	}
   708 	break;
   709       }
   710     case GEN_FLOW:
   711       {
   712 	NodeIt v;
   713 	for(g->first(v); g->valid(v); g->next(v)) excess.set(v,0);
   714 
   715 	Num exc=0;
   716 	InEdgeIt e;
   717 	for(g->first(e,t); g->valid(e); g->next(e)) exc+=(*flow)[e];
   718 	OutEdgeIt f;
   719 	for(g->first(f,t); g->valid(f); g->next(f)) exc-=(*flow)[f];
   720 	excess.set(t,exc);
   721 	break;
   722       }
   723     case ZERO_FLOW:
   724     case NO_FLOW:
   725       {
   726 	NodeIt v;
   727         for(g->first(v); g->valid(v); g->next(v)) excess.set(v,0);
   728 	break;
   729       }
   730     }
   731 
   732     preflowPreproc(fe, active, level_list, left, right);
   733     //End of preprocessing
   734 
   735 
   736     //Push/relabel on the highest level active nodes.
   737     while ( true ) {
   738       if ( b == 0 ) {
   739 	if ( !what_heur && !end && k > 0 ) {
   740 	  b=k;
   741 	  end=true;
   742 	} else break;
   743       }
   744 
   745       if ( active[b].empty() ) --b;
   746       else {
   747 	end=false;
   748 	Node w=active[b].top();
   749 	active[b].pop();
   750 	int newlevel=push(w,active);
   751 	if ( excess[w] > 0 ) relabel(w, newlevel, active, level_list,
   752 				     left, right, b, k, what_heur);
   753 
   754 	++numrelabel;
   755 	if ( numrelabel >= heur ) {
   756 	  numrelabel=0;
   757 	  if ( what_heur ) {
   758 	    what_heur=0;
   759 	    heur=heur0;
   760 	    end=false;
   761 	  } else {
   762 	    what_heur=1;
   763 	    heur=heur1;
   764 	    b=k;
   765 	  }
   766 	}
   767       }
   768     }
   769   }
   770 
   771 
   772 
   773   template <typename Graph, typename Num, typename CapMap, typename FlowMap>
   774   void MaxFlow<Graph, Num, CapMap, FlowMap>::preflowPhase2()
   775   {
   776 
   777     int k=n-2;  //bound on the highest level under n containing a node
   778     int b=k;    //bound on the highest level under n of an active node
   779 
   780     VecStack active(n);
   781     level.set(s,0);
   782     std::queue<Node> bfs_queue;
   783     bfs_queue.push(s);
   784 
   785     while (!bfs_queue.empty()) {
   786 
   787       Node v=bfs_queue.front();
   788       bfs_queue.pop();
   789       int l=level[v]+1;
   790 
   791       InEdgeIt e;
   792       for(g->first(e,v); g->valid(e); g->next(e)) {
   793 	if ( (*capacity)[e] <= (*flow)[e] ) continue;
   794 	Node u=g->tail(e);
   795 	if ( level[u] >= n ) {
   796 	  bfs_queue.push(u);
   797 	  level.set(u, l);
   798 	  if ( excess[u] > 0 ) active[l].push(u);
   799 	}
   800       }
   801 
   802       OutEdgeIt f;
   803       for(g->first(f,v); g->valid(f); g->next(f)) {
   804 	if ( 0 >= (*flow)[f] ) continue;
   805 	Node u=g->head(f);
   806 	if ( level[u] >= n ) {
   807 	  bfs_queue.push(u);
   808 	  level.set(u, l);
   809 	  if ( excess[u] > 0 ) active[l].push(u);
   810 	}
   811       }
   812     }
   813     b=n-2;
   814 
   815     while ( true ) {
   816 
   817       if ( b == 0 ) break;
   818 
   819       if ( active[b].empty() ) --b;
   820       else {
   821 	Node w=active[b].top();
   822 	active[b].pop();
   823 	int newlevel=push(w,active);
   824 
   825 	//relabel
   826 	if ( excess[w] > 0 ) {
   827 	  level.set(w,++newlevel);
   828 	  active[newlevel].push(w);
   829 	  b=newlevel;
   830 	}
   831       }  // if stack[b] is nonempty
   832     } // while(true)
   833   }
   834 
   835 
   836 
   837   template <typename Graph, typename Num, typename CapMap, typename FlowMap>
   838   bool MaxFlow<Graph, Num, CapMap, FlowMap>::augmentOnShortestPath()
   839   {
   840     ResGW res_graph(*g, *capacity, *flow);
   841     bool _augment=false;
   842 
   843     //ReachedMap level(res_graph);
   844     FOR_EACH_LOC(typename Graph::NodeIt, e, *g) level.set(e, 0);
   845     BfsIterator<ResGW, ReachedMap> bfs(res_graph, level);
   846     bfs.pushAndSetReached(s);
   847 
   848     typename ResGW::template NodeMap<ResGWEdge> pred(res_graph);
   849     pred.set(s, INVALID);
   850 
   851     typename ResGW::template NodeMap<Num> free(res_graph);
   852 
   853     //searching for augmenting path
   854     while ( !bfs.finished() ) {
   855       ResGWOutEdgeIt e=bfs;
   856       if (res_graph.valid(e) && bfs.isBNodeNewlyReached()) {
   857 	Node v=res_graph.tail(e);
   858 	Node w=res_graph.head(e);
   859 	pred.set(w, e);
   860 	if (res_graph.valid(pred[v])) {
   861 	  free.set(w, std::min(free[v], res_graph.resCap(e)));
   862 	} else {
   863 	  free.set(w, res_graph.resCap(e));
   864 	}
   865 	if (res_graph.head(e)==t) { _augment=true; break; }
   866       }
   867 
   868       ++bfs;
   869     } //end of searching augmenting path
   870 
   871     if (_augment) {
   872       Node n=t;
   873       Num augment_value=free[t];
   874       while (res_graph.valid(pred[n])) {
   875 	ResGWEdge e=pred[n];
   876 	res_graph.augment(e, augment_value);
   877 	n=res_graph.tail(e);
   878       }
   879     }
   880 
   881     return _augment;
   882   }
   883 
   884 
   885 
   886 
   887 
   888 
   889 
   890   template <typename Graph, typename Num, typename CapMap, typename FlowMap>
   891   template<typename MutableGraph>
   892   bool MaxFlow<Graph, Num, CapMap, FlowMap>::augmentOnBlockingFlow()
   893   {
   894     typedef MutableGraph MG;
   895     bool _augment=false;
   896 
   897     ResGW res_graph(*g, *capacity, *flow);
   898 
   899     //bfs for distances on the residual graph
   900     //ReachedMap level(res_graph);
   901     FOR_EACH_LOC(typename Graph::NodeIt, e, *g) level.set(e, 0);
   902     BfsIterator<ResGW, ReachedMap> bfs(res_graph, level);
   903     bfs.pushAndSetReached(s);
   904     typename ResGW::template NodeMap<int>
   905       dist(res_graph); //filled up with 0's
   906 
   907     //F will contain the physical copy of the residual graph
   908     //with the set of edges which are on shortest paths
   909     MG F;
   910     typename ResGW::template NodeMap<typename MG::Node>
   911       res_graph_to_F(res_graph);
   912     {
   913       typename ResGW::NodeIt n;
   914       for(res_graph.first(n); res_graph.valid(n); res_graph.next(n)) {
   915 	res_graph_to_F.set(n, F.addNode());
   916       }
   917     }
   918 
   919     typename MG::Node sF=res_graph_to_F[s];
   920     typename MG::Node tF=res_graph_to_F[t];
   921     typename MG::template EdgeMap<ResGWEdge> original_edge(F);
   922     typename MG::template EdgeMap<Num> residual_capacity(F);
   923 
   924     while ( !bfs.finished() ) {
   925       ResGWOutEdgeIt e=bfs;
   926       if (res_graph.valid(e)) {
   927 	if (bfs.isBNodeNewlyReached()) {
   928 	  dist.set(res_graph.head(e), dist[res_graph.tail(e)]+1);
   929 	  typename MG::Edge f=F.addEdge(res_graph_to_F[res_graph.tail(e)],
   930 					res_graph_to_F[res_graph.head(e)]);
   931 	  original_edge.update();
   932 	  original_edge.set(f, e);
   933 	  residual_capacity.update();
   934 	  residual_capacity.set(f, res_graph.resCap(e));
   935 	} else {
   936 	  if (dist[res_graph.head(e)]==(dist[res_graph.tail(e)]+1)) {
   937 	    typename MG::Edge f=F.addEdge(res_graph_to_F[res_graph.tail(e)],
   938 					  res_graph_to_F[res_graph.head(e)]);
   939 	    original_edge.update();
   940 	    original_edge.set(f, e);
   941 	    residual_capacity.update();
   942 	    residual_capacity.set(f, res_graph.resCap(e));
   943 	  }
   944 	}
   945       }
   946       ++bfs;
   947     } //computing distances from s in the residual graph
   948 
   949     bool __augment=true;
   950 
   951     while (__augment) {
   952       __augment=false;
   953       //computing blocking flow with dfs
   954       DfsIterator< MG, typename MG::template NodeMap<bool> > dfs(F);
   955       typename MG::template NodeMap<typename MG::Edge> pred(F);
   956       pred.set(sF, INVALID);
   957       //invalid iterators for sources
   958 
   959       typename MG::template NodeMap<Num> free(F);
   960 
   961       dfs.pushAndSetReached(sF);
   962       while (!dfs.finished()) {
   963 	++dfs;
   964 	if (F.valid(/*typename MG::OutEdgeIt*/(dfs))) {
   965 	  if (dfs.isBNodeNewlyReached()) {
   966 	    typename MG::Node v=F.aNode(dfs);
   967 	    typename MG::Node w=F.bNode(dfs);
   968 	    pred.set(w, dfs);
   969 	    if (F.valid(pred[v])) {
   970 	      free.set(w, std::min(free[v], residual_capacity[dfs]));
   971 	    } else {
   972 	      free.set(w, residual_capacity[dfs]);
   973 	    }
   974 	    if (w==tF) {
   975 	      __augment=true;
   976 	      _augment=true;
   977 	      break;
   978 	    }
   979 
   980 	  } else {
   981 	    F.erase(/*typename MG::OutEdgeIt*/(dfs));
   982 	  }
   983 	}
   984       }
   985 
   986       if (__augment) {
   987 	typename MG::Node n=tF;
   988 	Num augment_value=free[tF];
   989 	while (F.valid(pred[n])) {
   990 	  typename MG::Edge e=pred[n];
   991 	  res_graph.augment(original_edge[e], augment_value);
   992 	  n=F.tail(e);
   993 	  if (residual_capacity[e]==augment_value)
   994 	    F.erase(e);
   995 	  else
   996 	    residual_capacity.set(e, residual_capacity[e]-augment_value);
   997 	}
   998       }
   999 
  1000     }
  1001 
  1002     return _augment;
  1003   }
  1004 
  1005 
  1006 
  1007 
  1008   template <typename Graph, typename Num, typename CapMap, typename FlowMap>
  1009   bool MaxFlow<Graph, Num, CapMap, FlowMap>::augmentOnBlockingFlow2()
  1010   {
  1011     bool _augment=false;
  1012 
  1013     ResGW res_graph(*g, *capacity, *flow);
  1014 
  1015     //ReachedMap level(res_graph);
  1016     FOR_EACH_LOC(typename Graph::NodeIt, e, *g) level.set(e, 0);
  1017     BfsIterator<ResGW, ReachedMap> bfs(res_graph, level);
  1018 
  1019     bfs.pushAndSetReached(s);
  1020     DistanceMap<ResGW> dist(res_graph);
  1021     while ( !bfs.finished() ) {
  1022       ResGWOutEdgeIt e=bfs;
  1023       if (res_graph.valid(e) && bfs.isBNodeNewlyReached()) {
  1024 	dist.set(res_graph.head(e), dist[res_graph.tail(e)]+1);
  1025       }
  1026       ++bfs;
  1027     } //computing distances from s in the residual graph
  1028 
  1029       //Subgraph containing the edges on some shortest paths
  1030     ConstMap<typename ResGW::Node, bool> true_map(true);
  1031     typedef SubGraphWrapper<ResGW, ConstMap<typename ResGW::Node, bool>,
  1032       DistanceMap<ResGW> > FilterResGW;
  1033     FilterResGW filter_res_graph(res_graph, true_map, dist);
  1034 
  1035     //Subgraph, which is able to delete edges which are already
  1036     //met by the dfs
  1037     typename FilterResGW::template NodeMap<typename FilterResGW::OutEdgeIt>
  1038       first_out_edges(filter_res_graph);
  1039     typename FilterResGW::NodeIt v;
  1040     for(filter_res_graph.first(v); filter_res_graph.valid(v);
  1041 	filter_res_graph.next(v))
  1042       {
  1043  	typename FilterResGW::OutEdgeIt e;
  1044  	filter_res_graph.first(e, v);
  1045  	first_out_edges.set(v, e);
  1046       }
  1047     typedef ErasingFirstGraphWrapper<FilterResGW, typename FilterResGW::
  1048       template NodeMap<typename FilterResGW::OutEdgeIt> > ErasingResGW;
  1049     ErasingResGW erasing_res_graph(filter_res_graph, first_out_edges);
  1050 
  1051     bool __augment=true;
  1052 
  1053     while (__augment) {
  1054 
  1055       __augment=false;
  1056       //computing blocking flow with dfs
  1057       DfsIterator< ErasingResGW,
  1058 	typename ErasingResGW::template NodeMap<bool> >
  1059 	dfs(erasing_res_graph);
  1060       typename ErasingResGW::
  1061 	template NodeMap<typename ErasingResGW::OutEdgeIt>
  1062 	pred(erasing_res_graph);
  1063       pred.set(s, INVALID);
  1064       //invalid iterators for sources
  1065 
  1066       typename ErasingResGW::template NodeMap<Num>
  1067 	free1(erasing_res_graph);
  1068 
  1069       dfs.pushAndSetReached
  1070 	///\bug hugo 0.2
  1071 	(typename ErasingResGW::Node
  1072 	 (typename FilterResGW::Node
  1073 	  (typename ResGW::Node(s)
  1074 	   )
  1075 	  )
  1076 	 );
  1077       while (!dfs.finished()) {
  1078 	++dfs;
  1079 	if (erasing_res_graph.valid(typename ErasingResGW::OutEdgeIt(dfs)))
  1080  	  {
  1081   	    if (dfs.isBNodeNewlyReached()) {
  1082 
  1083  	      typename ErasingResGW::Node v=erasing_res_graph.aNode(dfs);
  1084  	      typename ErasingResGW::Node w=erasing_res_graph.bNode(dfs);
  1085 
  1086  	      pred.set(w, /*typename ErasingResGW::OutEdgeIt*/(dfs));
  1087  	      if (erasing_res_graph.valid(pred[v])) {
  1088  		free1.set
  1089 		  (w, std::min(free1[v], res_graph.resCap
  1090 			       (typename ErasingResGW::OutEdgeIt(dfs))));
  1091  	      } else {
  1092  		free1.set
  1093 		  (w, res_graph.resCap
  1094 		   (typename ErasingResGW::OutEdgeIt(dfs)));
  1095  	      }
  1096 
  1097  	      if (w==t) {
  1098  		__augment=true;
  1099  		_augment=true;
  1100  		break;
  1101  	      }
  1102  	    } else {
  1103  	      erasing_res_graph.erase(dfs);
  1104 	    }
  1105 	  }
  1106       }
  1107 
  1108       if (__augment) {
  1109 	typename ErasingResGW::Node
  1110 	  n=typename FilterResGW::Node(typename ResGW::Node(t));
  1111 	// 	  typename ResGW::NodeMap<Num> a(res_graph);
  1112 	// 	  typename ResGW::Node b;
  1113 	// 	  Num j=a[b];
  1114 	// 	  typename FilterResGW::NodeMap<Num> a1(filter_res_graph);
  1115 	// 	  typename FilterResGW::Node b1;
  1116 	// 	  Num j1=a1[b1];
  1117 	// 	  typename ErasingResGW::NodeMap<Num> a2(erasing_res_graph);
  1118 	// 	  typename ErasingResGW::Node b2;
  1119 	// 	  Num j2=a2[b2];
  1120 	Num augment_value=free1[n];
  1121 	while (erasing_res_graph.valid(pred[n])) {
  1122 	  typename ErasingResGW::OutEdgeIt e=pred[n];
  1123 	  res_graph.augment(e, augment_value);
  1124 	  n=erasing_res_graph.tail(e);
  1125 	  if (res_graph.resCap(e)==0)
  1126 	    erasing_res_graph.erase(e);
  1127 	}
  1128       }
  1129 
  1130     } //while (__augment)
  1131 
  1132     return _augment;
  1133   }
  1134 
  1135 
  1136 } //namespace hugo
  1137 
  1138 #endif //HUGO_MAX_FLOW_H
  1139 
  1140 
  1141 
  1142