0
2
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... | ... |
@@ -31,2 +31,3 @@ |
31 | 31 |
#include <lemon/list_graph.h> |
32 |
#include <lemon/dijkstra.h> |
|
32 | 33 |
#include <lemon/maps.h> |
... | ... |
@@ -48,3 +49,3 @@ |
48 | 49 |
/// efficient specialized version of the \ref CapacityScaling |
49 |
/// " |
|
50 |
/// "successive shortest path" algorithm directly for this problem. |
|
50 | 51 |
/// Therefore this class provides query functions for flow values and |
... | ... |
@@ -57,5 +58,5 @@ |
57 | 58 |
/// |
58 |
/// \warning Length values should be \e non-negative |
|
59 |
/// \warning Length values should be \e non-negative. |
|
59 | 60 |
/// |
60 |
/// \note For finding node-disjoint paths this algorithm can be used |
|
61 |
/// \note For finding \e node-disjoint paths, this algorithm can be used |
|
61 | 62 |
/// along with the \ref SplitNodes adaptor. |
... | ... |
@@ -99,2 +100,5 @@ |
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 |
... | ... |
@@ -106,24 +110,14 @@ |
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 on |
|
113 | 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) nodes |
|
125 |
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 |
|
... | ... |
@@ -131,15 +125,19 @@ |
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 |
|
|
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 |
} |
|
141 | 137 |
|
142 |
/// \brief Run the algorithm. It returns \c true if a path is found |
|
143 |
/// from the source node to the target node. |
|
144 |
|
|
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); |
... | ... |
@@ -153,6 +151,51 @@ |
153 | 151 |
Node u = heap.top(), v; |
154 |
Length d = heap.prio() |
|
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 |
|
... | ... |
@@ -163,15 +206,15 @@ |
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 |
} |
... | ... |
@@ -185,15 +228,15 @@ |
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 |
} |
... | ... |
@@ -207,3 +250,3 @@ |
207 | 250 |
for (int i = 0; i < int(_proc_nodes.size()); ++i) |
208 |
|
|
251 |
_pi[_proc_nodes[i]] += _dist[_proc_nodes[i]] - t_dist; |
|
209 | 252 |
return true; |
... | ... |
@@ -228,8 +271,8 @@ |
228 | 271 |
// The source node |
229 |
Node |
|
272 |
Node _s; |
|
230 | 273 |
// The target node |
231 |
Node |
|
274 |
Node _t; |
|
232 | 275 |
|
233 | 276 |
// Container to store the found paths |
234 |
std::vector< |
|
277 |
std::vector<Path> _paths; |
|
235 | 278 |
int _path_num; |
... | ... |
@@ -238,5 +281,7 @@ |
238 | 281 |
PredMap _pred; |
239 |
// Implementation of the Dijkstra algorithm for finding augmenting |
|
240 |
// shortest paths in the residual network |
|
241 |
|
|
282 |
|
|
283 |
// Data for full init |
|
284 |
PotentialMap *_init_dist; |
|
285 |
PredMap *_init_pred; |
|
286 |
bool _full_init; |
|
242 | 287 |
|
... | ... |
@@ -253,7 +298,5 @@ |
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 |
|
... | ... |
@@ -263,3 +306,4 @@ |
263 | 306 |
if (_local_potential) delete _potential; |
264 |
delete |
|
307 |
delete _init_dist; |
|
308 |
delete _init_pred; |
|
265 | 309 |
} |
... | ... |
@@ -308,6 +352,9 @@ |
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 |
|
358 |
/// arc-disjoint paths, then you may call findFlow() instead of |
|
359 |
/// start(). |
|
313 | 360 |
|
... | ... |
@@ -331,4 +378,3 @@ |
331 | 378 |
/// s.init(s); |
332 |
/// s.findFlow(t, k); |
|
333 |
/// s.findPaths(); |
|
379 |
/// s.start(t, k); |
|
334 | 380 |
/// \endcode |
... | ... |
@@ -336,4 +382,3 @@ |
336 | 382 |
init(s); |
337 |
findFlow(t, k); |
|
338 |
findPaths(); |
|
383 |
start(t, k); |
|
339 | 384 |
return _path_num; |
... | ... |
@@ -343,3 +388,3 @@ |
343 | 388 |
/// |
344 |
/// This function initializes the algorithm. |
|
389 |
/// This function initializes the algorithm with the given source node. |
|
345 | 390 |
/// |
... | ... |
@@ -347,3 +392,3 @@ |
347 | 392 |
void init(const Node& s) { |
348 |
|
|
393 |
_s = s; |
|
349 | 394 |
|
... | ... |
@@ -358,4 +403,59 @@ |
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 |
} |
... | ... |
@@ -377,12 +477,31 @@ |
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 (! |
|
506 |
if (!dijkstra.run(_path_num)) break; |
|
388 | 507 |
++_path_num; |
... | ... |
@@ -390,3 +509,3 @@ |
390 | 509 |
// Set the flow along the found shortest path |
391 |
Node u = |
|
510 |
Node u = _t; |
|
392 | 511 |
Arc e; |
... | ... |
@@ -407,4 +526,4 @@ |
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 |
/// |
... | ... |
@@ -416,7 +535,7 @@ |
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 = _source; |
|
421 |
while (n != _target) { |
|
539 |
Node n = _s; |
|
540 |
while (n != _t) { |
|
422 | 541 |
OutArcIt e(_graph, n); |
... | ... |
@@ -424,3 +543,3 @@ |
424 | 543 |
n = _graph.target(e); |
425 |
|
|
544 |
_paths[i].addBack(e); |
|
426 | 545 |
res_flow[e] = 0; |
... | ... |
@@ -522,4 +641,4 @@ |
522 | 641 |
/// this function. |
523 |
Path path(int i) const { |
|
524 |
return paths[i]; |
|
642 |
const Path& path(int i) const { |
|
643 |
return _paths[i]; |
|
525 | 644 |
} |
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