1 /* -*- mode: C++; indent-tabs-mode: nil; -*-
3 * This file is a part of LEMON, a generic C++ optimization library.
5 * Copyright (C) 2003-2011
6 * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
7 * (Egervary Research Group on Combinatorial Optimization, EGRES).
9 * Permission to use, modify and distribute this software is granted
10 * provided that this copyright notice appears in all copies. For
11 * precise terms see the accompanying LICENSE file.
13 * This software is provided "AS IS" with no warranty of any kind,
14 * express or implied, and with no claim as to its suitability for any
22 @defgroup datas Data Structures
23 This group contains the several data structures implemented in LEMON.
27 @defgroup graphs Graph Structures
29 \brief Graph structures implemented in LEMON.
31 The implementation of combinatorial algorithms heavily relies on
32 efficient graph implementations. LEMON offers data structures which are
33 planned to be easily used in an experimental phase of implementation studies,
34 and thereafter the program code can be made efficient by small modifications.
36 The most efficient implementation of diverse applications require the
37 usage of different physical graph implementations. These differences
38 appear in the size of graph we require to handle, memory or time usage
39 limitations or in the set of operations through which the graph can be
40 accessed. LEMON provides several physical graph structures to meet
41 the diverging requirements of the possible users. In order to save on
42 running time or on memory usage, some structures may fail to provide
43 some graph features like arc/edge or node deletion.
45 Alteration of standard containers need a very limited number of
46 operations, these together satisfy the everyday requirements.
47 In the case of graph structures, different operations are needed which do
48 not alter the physical graph, but gives another view. If some nodes or
49 arcs have to be hidden or the reverse oriented graph have to be used, then
50 this is the case. It also may happen that in a flow implementation
51 the residual graph can be accessed by another algorithm, or a node-set
52 is to be shrunk for another algorithm.
53 LEMON also provides a variety of graphs for these requirements called
54 \ref graph_adaptors "graph adaptors". Adaptors cannot be used alone but only
55 in conjunction with other graph representations.
57 You are free to use the graph structure that fit your requirements
58 the best, most graph algorithms and auxiliary data structures can be used
59 with any graph structure.
61 <b>See also:</b> \ref graph_concepts "Graph Structure Concepts".
65 @defgroup graph_adaptors Adaptor Classes for Graphs
67 \brief Adaptor classes for digraphs and graphs
69 This group contains several useful adaptor classes for digraphs and graphs.
71 The main parts of LEMON are the different graph structures, generic
72 graph algorithms, graph concepts, which couple them, and graph
73 adaptors. While the previous notions are more or less clear, the
74 latter one needs further explanation. Graph adaptors are graph classes
75 which serve for considering graph structures in different ways.
77 A short example makes this much clearer. Suppose that we have an
78 instance \c g of a directed graph type, say ListDigraph and an algorithm
80 template <typename Digraph>
81 int algorithm(const Digraph&);
83 is needed to run on the reverse oriented graph. It may be expensive
84 (in time or in memory usage) to copy \c g with the reversed
85 arcs. In this case, an adaptor class is used, which (according
86 to LEMON \ref concepts::Digraph "digraph concepts") works as a digraph.
87 The adaptor uses the original digraph structure and digraph operations when
88 methods of the reversed oriented graph are called. This means that the adaptor
89 have minor memory usage, and do not perform sophisticated algorithmic
90 actions. The purpose of it is to give a tool for the cases when a
91 graph have to be used in a specific alteration. If this alteration is
92 obtained by a usual construction like filtering the node or the arc set or
93 considering a new orientation, then an adaptor is worthwhile to use.
94 To come back to the reverse oriented graph, in this situation
96 template<typename Digraph> class ReverseDigraph;
98 template class can be used. The code looks as follows
101 ReverseDigraph<ListDigraph> rg(g);
102 int result = algorithm(rg);
104 During running the algorithm, the original digraph \c g is untouched.
105 This techniques give rise to an elegant code, and based on stable
106 graph adaptors, complex algorithms can be implemented easily.
108 In flow, circulation and matching problems, the residual
109 graph is of particular importance. Combining an adaptor implementing
110 this with shortest path algorithms or minimum mean cycle algorithms,
111 a range of weighted and cardinality optimization algorithms can be
112 obtained. For other examples, the interested user is referred to the
113 detailed documentation of particular adaptors.
115 The behavior of graph adaptors can be very different. Some of them keep
116 capabilities of the original graph while in other cases this would be
117 meaningless. This means that the concepts that they meet depend
118 on the graph adaptor, and the wrapped graph.
119 For example, if an arc of a reversed digraph is deleted, this is carried
120 out by deleting the corresponding arc of the original digraph, thus the
121 adaptor modifies the original digraph.
122 However in case of a residual digraph, this operation has no sense.
124 Let us stand one more example here to simplify your work.
125 ReverseDigraph has constructor
127 ReverseDigraph(Digraph& digraph);
129 This means that in a situation, when a <tt>const %ListDigraph&</tt>
130 reference to a graph is given, then it have to be instantiated with
131 <tt>Digraph=const %ListDigraph</tt>.
133 int algorithm1(const ListDigraph& g) {
134 ReverseDigraph<const ListDigraph> rg(g);
135 return algorithm2(rg);
143 \brief Map structures implemented in LEMON.
145 This group contains the map structures implemented in LEMON.
147 LEMON provides several special purpose maps and map adaptors that e.g. combine
148 new maps from existing ones.
150 <b>See also:</b> \ref map_concepts "Map Concepts".
154 @defgroup graph_maps Graph Maps
156 \brief Special graph-related maps.
158 This group contains maps that are specifically designed to assign
159 values to the nodes and arcs/edges of graphs.
161 If you are looking for the standard graph maps (\c NodeMap, \c ArcMap,
162 \c EdgeMap), see the \ref graph_concepts "Graph Structure Concepts".
166 \defgroup map_adaptors Map Adaptors
168 \brief Tools to create new maps from existing ones
170 This group contains map adaptors that are used to create "implicit"
171 maps from other maps.
173 Most of them are \ref concepts::ReadMap "read-only maps".
174 They can make arithmetic and logical operations between one or two maps
175 (negation, shifting, addition, multiplication, logical 'and', 'or',
176 'not' etc.) or e.g. convert a map to another one of different Value type.
178 The typical usage of this classes is passing implicit maps to
179 algorithms. If a function type algorithm is called then the function
180 type map adaptors can be used comfortable. For example let's see the
181 usage of map adaptors with the \c graphToEps() function.
183 Color nodeColor(int deg) {
185 return Color(0.5, 0.0, 0.5);
186 } else if (deg == 1) {
187 return Color(1.0, 0.5, 1.0);
189 return Color(0.0, 0.0, 0.0);
193 Digraph::NodeMap<int> degree_map(graph);
195 graphToEps(graph, "graph.eps")
196 .coords(coords).scaleToA4().undirected()
197 .nodeColors(composeMap(functorToMap(nodeColor), degree_map))
200 The \c functorToMap() function makes an \c int to \c Color map from the
201 \c nodeColor() function. The \c composeMap() compose the \c degree_map
202 and the previously created map. The composed map is a proper function to
203 get the color of each node.
205 The usage with class type algorithms is little bit harder. In this
206 case the function type map adaptors can not be used, because the
207 function map adaptors give back temporary objects.
211 typedef Digraph::ArcMap<double> DoubleArcMap;
212 DoubleArcMap length(graph);
213 DoubleArcMap speed(graph);
215 typedef DivMap<DoubleArcMap, DoubleArcMap> TimeMap;
216 TimeMap time(length, speed);
218 Dijkstra<Digraph, TimeMap> dijkstra(graph, time);
219 dijkstra.run(source, target);
221 We have a length map and a maximum speed map on the arcs of a digraph.
222 The minimum time to pass the arc can be calculated as the division of
223 the two maps which can be done implicitly with the \c DivMap template
224 class. We use the implicit minimum time map as the length map of the
225 \c Dijkstra algorithm.
229 @defgroup paths Path Structures
231 \brief %Path structures implemented in LEMON.
233 This group contains the path structures implemented in LEMON.
235 LEMON provides flexible data structures to work with paths.
236 All of them have similar interfaces and they can be copied easily with
237 assignment operators and copy constructors. This makes it easy and
238 efficient to have e.g. the Dijkstra algorithm to store its result in
239 any kind of path structure.
241 \sa lemon::concepts::Path
245 @defgroup auxdat Auxiliary Data Structures
247 \brief Auxiliary data structures implemented in LEMON.
249 This group contains some data structures implemented in LEMON in
250 order to make it easier to implement combinatorial algorithms.
254 @defgroup algs Algorithms
255 \brief This group contains the several algorithms
256 implemented in LEMON.
258 This group contains the several algorithms
259 implemented in LEMON.
263 @defgroup search Graph Search
265 \brief Common graph search algorithms.
267 This group contains the common graph search algorithms, namely
268 \e breadth-first \e search (BFS) and \e depth-first \e search (DFS).
272 @defgroup shortest_path Shortest Path Algorithms
274 \brief Algorithms for finding shortest paths.
276 This group contains the algorithms for finding shortest paths in digraphs.
278 - \ref Dijkstra Dijkstra's algorithm for finding shortest paths from a
279 source node when all arc lengths are non-negative.
280 - \ref Suurballe A successive shortest path algorithm for finding
281 arc-disjoint paths between two nodes having minimum total length.
285 @defgroup max_flow Maximum Flow Algorithms
287 \brief Algorithms for finding maximum flows.
289 This group contains the algorithms for finding maximum flows and
290 feasible circulations.
292 The \e maximum \e flow \e problem is to find a flow of maximum value between
293 a single source and a single target. Formally, there is a \f$G=(V,A)\f$
294 digraph, a \f$cap: A\rightarrow\mathbf{R}^+_0\f$ capacity function and
295 \f$s, t \in V\f$ source and target nodes.
296 A maximum flow is an \f$f: A\rightarrow\mathbf{R}^+_0\f$ solution of the
297 following optimization problem.
299 \f[ \max\sum_{sv\in A} f(sv) - \sum_{vs\in A} f(vs) \f]
300 \f[ \sum_{uv\in A} f(uv) = \sum_{vu\in A} f(vu)
301 \quad \forall u\in V\setminus\{s,t\} \f]
302 \f[ 0 \leq f(uv) \leq cap(uv) \quad \forall uv\in A \f]
304 \ref Preflow implements the preflow push-relabel algorithm of Goldberg and
305 Tarjan for solving this problem. It also provides functions to query the
306 minimum cut, which is the dual problem of maximum flow.
309 \ref Circulation is a preflow push-relabel algorithm implemented directly
310 for finding feasible circulations, which is a somewhat different problem,
311 but it is strongly related to maximum flow.
312 For more information, see \ref Circulation.
316 @defgroup min_cost_flow_algs Minimum Cost Flow Algorithms
319 \brief Algorithms for finding minimum cost flows and circulations.
321 This group contains the algorithms for finding minimum cost flows and
322 circulations. For more information about this problem and its dual
323 solution see \ref min_cost_flow "Minimum Cost Flow Problem".
325 \ref NetworkSimplex is an efficient implementation of the primal Network
326 Simplex algorithm for finding minimum cost flows. It also provides dual
327 solution (node potentials), if an optimal flow is found.
331 @defgroup min_cut Minimum Cut Algorithms
334 \brief Algorithms for finding minimum cut in graphs.
336 This group contains the algorithms for finding minimum cut in graphs.
338 The \e minimum \e cut \e problem is to find a non-empty and non-complete
339 \f$X\f$ subset of the nodes with minimum overall capacity on
340 outgoing arcs. Formally, there is a \f$G=(V,A)\f$ digraph, a
341 \f$cap: A\rightarrow\mathbf{R}^+_0\f$ capacity function. The minimum
342 cut is the \f$X\f$ solution of the next optimization problem:
344 \f[ \min_{X \subset V, X\not\in \{\emptyset, V\}}
345 \sum_{uv\in A, u\in X, v\not\in X}cap(uv) \f]
347 LEMON contains several algorithms related to minimum cut problems:
349 - \ref HaoOrlin "Hao-Orlin algorithm" for calculating minimum cut
351 - \ref GomoryHu "Gomory-Hu tree computation" for calculating
352 all-pairs minimum cut in undirected graphs.
354 If you want to find minimum cut just between two distinict nodes,
355 see the \ref max_flow "maximum flow problem".
359 @defgroup graph_properties Connectivity and Other Graph Properties
361 \brief Algorithms for discovering the graph properties
363 This group contains the algorithms for discovering the graph properties
364 like connectivity, bipartiteness, euler property, simplicity etc.
366 \image html edge_biconnected_components.png
367 \image latex edge_biconnected_components.eps "bi-edge-connected components" width=\textwidth
371 @defgroup matching Matching Algorithms
373 \brief Algorithms for finding matchings in graphs and bipartite graphs.
375 This group contains the algorithms for calculating matchings in graphs.
376 The general matching problem is finding a subset of the edges for which
377 each node has at most one incident edge.
379 There are several different algorithms for calculate matchings in
380 graphs. The goal of the matching optimization
381 can be finding maximum cardinality, maximum weight or minimum cost
382 matching. The search can be constrained to find perfect or
383 maximum cardinality matching.
385 The matching algorithms implemented in LEMON:
386 - \ref MaxMatching Edmond's blossom shrinking algorithm for calculating
387 maximum cardinality matching in general graphs.
388 - \ref MaxWeightedMatching Edmond's blossom shrinking algorithm for calculating
389 maximum weighted matching in general graphs.
390 - \ref MaxWeightedPerfectMatching
391 Edmond's blossom shrinking algorithm for calculating maximum weighted
392 perfect matching in general graphs.
394 \image html bipartite_matching.png
395 \image latex bipartite_matching.eps "Bipartite Matching" width=\textwidth
399 @defgroup spantree Minimum Spanning Tree Algorithms
401 \brief Algorithms for finding minimum cost spanning trees and arborescences.
403 This group contains the algorithms for finding minimum cost spanning
404 trees and arborescences.
408 @defgroup auxalg Auxiliary Algorithms
410 \brief Auxiliary algorithms implemented in LEMON.
412 This group contains some algorithms implemented in LEMON
413 in order to make it easier to implement complex algorithms.
417 @defgroup gen_opt_group General Optimization Tools
418 \brief This group contains some general optimization frameworks
419 implemented in LEMON.
421 This group contains some general optimization frameworks
422 implemented in LEMON.
426 @defgroup lp_group Lp and Mip Solvers
427 @ingroup gen_opt_group
428 \brief Lp and Mip solver interfaces for LEMON.
430 This group contains Lp and Mip solver interfaces for LEMON. The
431 various LP solvers could be used in the same manner with this
436 @defgroup utils Tools and Utilities
437 \brief Tools and utilities for programming in LEMON
439 Tools and utilities for programming in LEMON.
443 @defgroup gutils Basic Graph Utilities
445 \brief Simple basic graph utilities.
447 This group contains some simple basic graph utilities.
451 @defgroup misc Miscellaneous Tools
453 \brief Tools for development, debugging and testing.
455 This group contains several useful tools for development,
456 debugging and testing.
460 @defgroup timecount Time Measuring and Counting
462 \brief Simple tools for measuring the performance of algorithms.
464 This group contains simple tools for measuring the performance
469 @defgroup exceptions Exceptions
471 \brief Exceptions defined in LEMON.
473 This group contains the exceptions defined in LEMON.
477 @defgroup io_group Input-Output
478 \brief Graph Input-Output methods
480 This group contains the tools for importing and exporting graphs
481 and graph related data. Now it supports the \ref lgf-format
482 "LEMON Graph Format", the \c DIMACS format and the encapsulated
483 postscript (EPS) format.
487 @defgroup lemon_io LEMON Graph Format
489 \brief Reading and writing LEMON Graph Format.
491 This group contains methods for reading and writing
492 \ref lgf-format "LEMON Graph Format".
496 @defgroup eps_io Postscript Exporting
498 \brief General \c EPS drawer and graph exporter
500 This group contains general \c EPS drawing methods and special
501 graph exporting tools.
505 @defgroup dimacs_group DIMACS format
507 \brief Read and write files in DIMACS format
509 Tools to read a digraph from or write it to a file in DIMACS format data.
513 @defgroup nauty_group NAUTY Format
515 \brief Read \e Nauty format
517 Tool to read graphs from \e Nauty format data.
521 @defgroup concept Concepts
522 \brief Skeleton classes and concept checking classes
524 This group contains the data/algorithm skeletons and concept checking
525 classes implemented in LEMON.
527 The purpose of the classes in this group is fourfold.
529 - These classes contain the documentations of the %concepts. In order
530 to avoid document multiplications, an implementation of a concept
531 simply refers to the corresponding concept class.
533 - These classes declare every functions, <tt>typedef</tt>s etc. an
534 implementation of the %concepts should provide, however completely
535 without implementations and real data structures behind the
536 interface. On the other hand they should provide nothing else. All
537 the algorithms working on a data structure meeting a certain concept
538 should compile with these classes. (Though it will not run properly,
539 of course.) In this way it is easily to check if an algorithm
540 doesn't use any extra feature of a certain implementation.
542 - The concept descriptor classes also provide a <em>checker class</em>
543 that makes it possible to check whether a certain implementation of a
544 concept indeed provides all the required features.
546 - Finally, They can serve as a skeleton of a new implementation of a concept.
550 @defgroup graph_concepts Graph Structure Concepts
552 \brief Skeleton and concept checking classes for graph structures
554 This group contains the skeletons and concept checking classes of LEMON's
555 graph structures and helper classes used to implement these.
559 @defgroup map_concepts Map Concepts
561 \brief Skeleton and concept checking classes for maps
563 This group contains the skeletons and concept checking classes of maps.
569 @defgroup demos Demo Programs
571 Some demo programs are listed here. Their full source codes can be found in
572 the \c demo subdirectory of the source tree.
574 In order to compile them, use the <tt>make demo</tt> or the
575 <tt>make check</tt> commands.
579 @defgroup tools Standalone Utility Applications
581 Some utility applications are listed here.
583 The standard compilation procedure (<tt>./configure;make</tt>) will compile