Changes in / [850:e77b621e6e7e:856:5df6a8f29d5e] in lemon-main
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lemon/suurballe.h
r623 r854 30 30 #include <lemon/path.h> 31 31 #include <lemon/list_graph.h> 32 #include <lemon/dijkstra.h> 32 33 #include <lemon/maps.h> 33 34 … … 47 48 /// "minimum cost flow problem". This implementation is actually an 48 49 /// efficient specialized version of the \ref CapacityScaling 49 /// " Successive Shortest Path" algorithm directly for this problem.50 /// "successive shortest path" algorithm directly for this problem. 50 51 /// Therefore this class provides query functions for flow values and 51 52 /// node potentials (the dual solution) just like the minimum cost flow … … 56 57 /// The default value is <tt>GR::ArcMap<int></tt>. 57 58 /// 58 /// \warning Length values should be \e non-negative \e integers.59 /// \warning Length values should be \e non-negative. 59 60 /// 60 /// \note For finding node-disjoint pathsthis algorithm can be used61 /// \note For finding \e node-disjoint paths, this algorithm can be used 61 62 /// along with the \ref SplitNodes adaptor. 62 63 #ifdef DOXYGEN … … 98 99 private: 99 100 101 typedef typename Digraph::template NodeMap<int> HeapCrossRef; 102 typedef BinHeap<Length, HeapCrossRef> Heap; 103 100 104 // ResidualDijkstra is a special implementation of the 101 105 // Dijkstra algorithm for finding shortest paths in the … … 105 109 class ResidualDijkstra 106 110 { 107 typedef typename Digraph::template NodeMap<int> HeapCrossRef;108 typedef BinHeap<Length, HeapCrossRef> Heap;109 110 111 private: 111 112 112 // The digraph the algorithm runs on113 113 const Digraph &_graph; 114 115 // The main maps 114 const LengthMap &_length; 116 115 const FlowMap &_flow; 117 const LengthMap &_length; 118 PotentialMap &_potential; 119 120 // The distance map 121 PotentialMap _dist; 122 // The pred arc map 116 PotentialMap &_pi; 123 117 PredMap &_pred; 124 // The processed (i.e. permanently labeled) nodes125 std::vector<Node> _proc_nodes;126 127 118 Node _s; 128 119 Node _t; 120 121 PotentialMap _dist; 122 std::vector<Node> _proc_nodes; 129 123 130 124 public: 131 125 132 /// Constructor. 133 ResidualDijkstra( const Digraph &graph, 134 const FlowMap &flow, 135 const LengthMap &length, 136 PotentialMap &potential, 137 PredMap &pred, 138 Node s, Node t ) : 139 _graph(graph), _flow(flow), _length(length), _potential(potential), 140 _dist(graph), _pred(pred), _s(s), _t(t) {} 141 142 /// \brief Run the algorithm. It returns \c true if a path is found 143 /// from the source node to the target node. 144 bool run() { 126 // Constructor 127 ResidualDijkstra(Suurballe &srb) : 128 _graph(srb._graph), _length(srb._length), 129 _flow(*srb._flow), _pi(*srb._potential), _pred(srb._pred), 130 _s(srb._s), _t(srb._t), _dist(_graph) {} 131 132 // Run the algorithm and return true if a path is found 133 // from the source node to the target node. 134 bool run(int cnt) { 135 return cnt == 0 ? startFirst() : start(); 136 } 137 138 private: 139 140 // Execute the algorithm for the first time (the flow and potential 141 // functions have to be identically zero). 142 bool startFirst() { 145 143 HeapCrossRef heap_cross_ref(_graph, Heap::PRE_HEAP); 146 144 Heap heap(heap_cross_ref); … … 152 150 while (!heap.empty() && heap.top() != _t) { 153 151 Node u = heap.top(), v; 154 Length d = heap.prio() + _potential[u], nd;152 Length d = heap.prio(), dn; 155 153 _dist[u] = heap.prio(); 154 _proc_nodes.push_back(u); 156 155 heap.pop(); 156 157 // Traverse outgoing arcs 158 for (OutArcIt e(_graph, u); e != INVALID; ++e) { 159 v = _graph.target(e); 160 switch(heap.state(v)) { 161 case Heap::PRE_HEAP: 162 heap.push(v, d + _length[e]); 163 _pred[v] = e; 164 break; 165 case Heap::IN_HEAP: 166 dn = d + _length[e]; 167 if (dn < heap[v]) { 168 heap.decrease(v, dn); 169 _pred[v] = e; 170 } 171 break; 172 case Heap::POST_HEAP: 173 break; 174 } 175 } 176 } 177 if (heap.empty()) return false; 178 179 // Update potentials of processed nodes 180 Length t_dist = heap.prio(); 181 for (int i = 0; i < int(_proc_nodes.size()); ++i) 182 _pi[_proc_nodes[i]] = _dist[_proc_nodes[i]] - t_dist; 183 return true; 184 } 185 186 // Execute the algorithm. 187 bool start() { 188 HeapCrossRef heap_cross_ref(_graph, Heap::PRE_HEAP); 189 Heap heap(heap_cross_ref); 190 heap.push(_s, 0); 191 _pred[_s] = INVALID; 192 _proc_nodes.clear(); 193 194 // Process nodes 195 while (!heap.empty() && heap.top() != _t) { 196 Node u = heap.top(), v; 197 Length d = heap.prio() + _pi[u], dn; 198 _dist[u] = heap.prio(); 157 199 _proc_nodes.push_back(u); 200 heap.pop(); 158 201 159 202 // Traverse outgoing arcs … … 162 205 v = _graph.target(e); 163 206 switch(heap.state(v)) { 164 case Heap::PRE_HEAP: 165 heap.push(v, d + _length[e] - _potential[v]); 166 _pred[v] = e; 167 break; 168 case Heap::IN_HEAP: 169 nd = d + _length[e] - _potential[v]; 170 if (nd < heap[v]) { 171 heap.decrease(v, nd); 207 case Heap::PRE_HEAP: 208 heap.push(v, d + _length[e] - _pi[v]); 172 209 _pred[v] = e; 173 } 174 break; 175 case Heap::POST_HEAP: 176 break; 210 break; 211 case Heap::IN_HEAP: 212 dn = d + _length[e] - _pi[v]; 213 if (dn < heap[v]) { 214 heap.decrease(v, dn); 215 _pred[v] = e; 216 } 217 break; 218 case Heap::POST_HEAP: 219 break; 177 220 } 178 221 } … … 184 227 v = _graph.source(e); 185 228 switch(heap.state(v)) { 186 case Heap::PRE_HEAP: 187 heap.push(v, d - _length[e] - _potential[v]); 188 _pred[v] = e; 189 break; 190 case Heap::IN_HEAP: 191 nd = d - _length[e] - _potential[v]; 192 if (nd < heap[v]) { 193 heap.decrease(v, nd); 229 case Heap::PRE_HEAP: 230 heap.push(v, d - _length[e] - _pi[v]); 194 231 _pred[v] = e; 195 } 196 break; 197 case Heap::POST_HEAP: 198 break; 232 break; 233 case Heap::IN_HEAP: 234 dn = d - _length[e] - _pi[v]; 235 if (dn < heap[v]) { 236 heap.decrease(v, dn); 237 _pred[v] = e; 238 } 239 break; 240 case Heap::POST_HEAP: 241 break; 199 242 } 200 243 } … … 206 249 Length t_dist = heap.prio(); 207 250 for (int i = 0; i < int(_proc_nodes.size()); ++i) 208 _p otential[_proc_nodes[i]] += _dist[_proc_nodes[i]] - t_dist;251 _pi[_proc_nodes[i]] += _dist[_proc_nodes[i]] - t_dist; 209 252 return true; 210 253 } … … 227 270 228 271 // The source node 229 Node _s ource;272 Node _s; 230 273 // The target node 231 Node _t arget;274 Node _t; 232 275 233 276 // Container to store the found paths 234 std::vector< SimplePath<Digraph> >paths;277 std::vector<Path> _paths; 235 278 int _path_num; 236 279 237 280 // The pred arc map 238 281 PredMap _pred; 239 // Implementation of the Dijkstra algorithm for finding augmenting 240 // shortest paths in the residual network 241 ResidualDijkstra *_dijkstra; 282 283 // Data for full init 284 PotentialMap *_init_dist; 285 PredMap *_init_pred; 286 bool _full_init; 242 287 243 288 public: … … 252 297 const LengthMap &length ) : 253 298 _graph(graph), _length(length), _flow(0), _local_flow(false), 254 _potential(0), _local_potential(false), _pred(graph) 255 { 256 LEMON_ASSERT(std::numeric_limits<Length>::is_integer, 257 "The length type of Suurballe must be integer"); 258 } 299 _potential(0), _local_potential(false), _pred(graph), 300 _init_dist(0), _init_pred(0) 301 {} 259 302 260 303 /// Destructor. … … 262 305 if (_local_flow) delete _flow; 263 306 if (_local_potential) delete _potential; 264 delete _dijkstra; 307 delete _init_dist; 308 delete _init_pred; 265 309 } 266 310 … … 307 351 /// \name Execution Control 308 352 /// The simplest way to execute the algorithm is to call the run() 309 /// function. 310 /// \n 353 /// function.\n 354 /// If you need to execute the algorithm many times using the same 355 /// source node, then you may call fullInit() once and start() 356 /// for each target node.\n 311 357 /// If you only need the flow that is the union of the found 312 /// arc-disjoint paths, you may call init() and findFlow(). 358 /// arc-disjoint paths, then you may call findFlow() instead of 359 /// start(). 313 360 314 361 /// @{ … … 330 377 /// \code 331 378 /// s.init(s); 332 /// s.findFlow(t, k); 333 /// s.findPaths(); 379 /// s.start(t, k); 334 380 /// \endcode 335 381 int run(const Node& s, const Node& t, int k = 2) { 336 382 init(s); 337 findFlow(t, k); 338 findPaths(); 383 start(t, k); 339 384 return _path_num; 340 385 } … … 342 387 /// \brief Initialize the algorithm. 343 388 /// 344 /// This function initializes the algorithm .389 /// This function initializes the algorithm with the given source node. 345 390 /// 346 391 /// \param s The source node. 347 392 void init(const Node& s) { 348 _s ource= s;393 _s = s; 349 394 350 395 // Initialize maps … … 357 402 _local_potential = true; 358 403 } 359 for (ArcIt e(_graph); e != INVALID; ++e) (*_flow)[e] = 0; 360 for (NodeIt n(_graph); n != INVALID; ++n) (*_potential)[n] = 0; 404 _full_init = false; 405 } 406 407 /// \brief Initialize the algorithm and perform Dijkstra. 408 /// 409 /// This function initializes the algorithm and performs a full 410 /// Dijkstra search from the given source node. It makes consecutive 411 /// executions of \ref start() "start(t, k)" faster, since they 412 /// have to perform %Dijkstra only k-1 times. 413 /// 414 /// This initialization is usually worth using instead of \ref init() 415 /// if the algorithm is executed many times using the same source node. 416 /// 417 /// \param s The source node. 418 void fullInit(const Node& s) { 419 // Initialize maps 420 init(s); 421 if (!_init_dist) { 422 _init_dist = new PotentialMap(_graph); 423 } 424 if (!_init_pred) { 425 _init_pred = new PredMap(_graph); 426 } 427 428 // Run a full Dijkstra 429 typename Dijkstra<Digraph, LengthMap> 430 ::template SetStandardHeap<Heap> 431 ::template SetDistMap<PotentialMap> 432 ::template SetPredMap<PredMap> 433 ::Create dijk(_graph, _length); 434 dijk.distMap(*_init_dist).predMap(*_init_pred); 435 dijk.run(s); 436 437 _full_init = true; 438 } 439 440 /// \brief Execute the algorithm. 441 /// 442 /// This function executes the algorithm. 443 /// 444 /// \param t The target node. 445 /// \param k The number of paths to be found. 446 /// 447 /// \return \c k if there are at least \c k arc-disjoint paths from 448 /// \c s to \c t in the digraph. Otherwise it returns the number of 449 /// arc-disjoint paths found. 450 /// 451 /// \note Apart from the return value, <tt>s.start(t, k)</tt> is 452 /// just a shortcut of the following code. 453 /// \code 454 /// s.findFlow(t, k); 455 /// s.findPaths(); 456 /// \endcode 457 int start(const Node& t, int k = 2) { 458 findFlow(t, k); 459 findPaths(); 460 return _path_num; 361 461 } 362 462 … … 376 476 /// \pre \ref init() must be called before using this function. 377 477 int findFlow(const Node& t, int k = 2) { 378 _target = t; 379 _dijkstra = 380 new ResidualDijkstra( _graph, *_flow, _length, *_potential, _pred, 381 _source, _target ); 478 _t = t; 479 ResidualDijkstra dijkstra(*this); 480 481 // Initialization 482 for (ArcIt e(_graph); e != INVALID; ++e) { 483 (*_flow)[e] = 0; 484 } 485 if (_full_init) { 486 for (NodeIt n(_graph); n != INVALID; ++n) { 487 (*_potential)[n] = (*_init_dist)[n]; 488 } 489 Node u = _t; 490 Arc e; 491 while ((e = (*_init_pred)[u]) != INVALID) { 492 (*_flow)[e] = 1; 493 u = _graph.source(e); 494 } 495 _path_num = 1; 496 } else { 497 for (NodeIt n(_graph); n != INVALID; ++n) { 498 (*_potential)[n] = 0; 499 } 500 _path_num = 0; 501 } 382 502 383 503 // Find shortest paths 384 _path_num = 0;385 504 while (_path_num < k) { 386 505 // Run Dijkstra 387 if (! _dijkstra->run()) break;506 if (!dijkstra.run(_path_num)) break; 388 507 ++_path_num; 389 508 390 509 // Set the flow along the found shortest path 391 Node u = _t arget;510 Node u = _t; 392 511 Arc e; 393 512 while ((e = _pred[u]) != INVALID) { … … 406 525 /// \brief Compute the paths from the flow. 407 526 /// 408 /// This function computes the paths from the found minimum cost flow,409 /// which is the union of some arc-disjoint paths.527 /// This function computes arc-disjoint paths from the found minimum 528 /// cost flow, which is the union of them. 410 529 /// 411 530 /// \pre \ref init() and \ref findFlow() must be called before using … … 415 534 for(ArcIt a(_graph); a != INVALID; ++a) res_flow[a] = (*_flow)[a]; 416 535 417 paths.clear();418 paths.resize(_path_num);536 _paths.clear(); 537 _paths.resize(_path_num); 419 538 for (int i = 0; i < _path_num; ++i) { 420 Node n = _s ource;421 while (n != _t arget) {539 Node n = _s; 540 while (n != _t) { 422 541 OutArcIt e(_graph, n); 423 542 for ( ; res_flow[e] == 0; ++e) ; 424 543 n = _graph.target(e); 425 paths[i].addBack(e);544 _paths[i].addBack(e); 426 545 res_flow[e] = 0; 427 546 } … … 521 640 /// \pre \ref run() or \ref findPaths() must be called before using 522 641 /// this function. 523 Pathpath(int i) const {524 return paths[i];642 const Path& path(int i) const { 643 return _paths[i]; 525 644 } 526 645 -
test/suurballe_test.cc
r623 r854 102 102 k = suurb_test.run(n, n, k); 103 103 suurb_test.init(n); 104 suurb_test.fullInit(n); 105 suurb_test.start(n); 106 suurb_test.start(n, k); 104 107 k = suurb_test.findFlow(n); 105 108 k = suurb_test.findFlow(n, k);
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