doc/groups.dox
author Alpar Juttner <alpar@cs.elte.hu>
Mon, 07 Jan 2008 19:22:09 +0100
changeset 40 8f4e8273a458
child 41 b11737922197
permissions -rw-r--r--
Several doc files ported from svn -r3436

- groups.dox contains several incomlete references
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/* -*- C++ -*-
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 *
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 * This file is a part of LEMON, a generic C++ optimization library
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 *
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 * Copyright (C) 2003-2008
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 * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
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 * (Egervary Research Group on Combinatorial Optimization, EGRES).
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 *
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 * Permission to use, modify and distribute this software is granted
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 * provided that this copyright notice appears in all copies. For
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 * precise terms see the accompanying LICENSE file.
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 *
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 * This software is provided "AS IS" with no warranty of any kind,
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 * express or implied, and with no claim as to its suitability for any
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 * purpose.
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 *
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 */
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/**
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@defgroup datas Data Structures
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This group describes the several graph structures implemented in LEMON.
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*/
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/**
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@defgroup graphs Graph Structures
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@ingroup datas
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\brief Graph structures implemented in LEMON.
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The implementation of combinatorial algorithms heavily relies on 
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efficient graph implementations. LEMON offers data structures which are 
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planned to be easily used in an experimental phase of implementation studies, 
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and thereafter the program code can be made efficient by small modifications. 
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The most efficient implementation of diverse applications require the
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usage of different physical graph implementations. These differences
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appear in the size of graph we require to handle, memory or time usage
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limitations or in the set of operations through which the graph can be
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accessed.  LEMON provides several physical graph structures to meet
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the diverging requirements of the possible users.  In order to save on
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running time or on memory usage, some structures may fail to provide
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some graph features like edge or node deletion.
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Alteration of standard containers need a very limited number of 
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operations, these together satisfy the everyday requirements. 
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In the case of graph structures, different operations are needed which do 
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not alter the physical graph, but gives another view. If some nodes or 
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edges have to be hidden or the reverse oriented graph have to be used, then 
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this is the case. It also may happen that in a flow implementation 
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the residual graph can be accessed by another algorithm, or a node-set 
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is to be shrunk for another algorithm. 
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LEMON also provides a variety of graphs for these requirements called 
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\ref graph_adaptors "graph adaptors". Adaptors cannot be used alone but only 
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in conjunction with other graph representation. 
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You are free to use the graph structure that fit your requirements
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the best, most graph algorithms and auxiliary data structures can be used
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with any graph structures. 
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*/
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/**
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@defgroup semi_adaptors Semi-Adaptors Classes for Graphs
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@ingroup graphs
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\brief Graph types between real graphs and graph adaptors.
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Graph types between real graphs and graph adaptors. These classes wrap
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graphs to give new functionality as the adaptors do it. On the other
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hand they are not light-weight structures as the adaptors.
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*/
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/**
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@defgroup maps Maps 
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@ingroup datas
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\brief Some special purpose map to make life easier.
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LEMON provides several special maps that e.g. combine
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new maps from existing ones.
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*/
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/**
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@defgroup graph_maps Graph Maps 
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@ingroup maps
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\brief Special Graph-Related Maps.
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These maps are specifically designed to assign values to the nodes and edges of
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graphs.
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*/
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/**
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\defgroup map_adaptors Map Adaptors
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\ingroup maps
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\brief Tools to create new maps from existing ones
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Map adaptors are used to create "implicit" maps from other maps.
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Most of them are \ref lemon::concepts::ReadMap "ReadMap"s. They can
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make arithmetic operations between one or two maps (negation, scaling,
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addition, multiplication etc.) or e.g. convert a map to another one
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of different Value type.
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The typical usage of this classes is the passing implicit maps to
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algorithms.  If a function type algorithm is called then the function
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type map adaptors can be used comfortable. For example let's see the
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usage of map adaptors with the \c graphToEps() function:
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\code
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  Color nodeColor(int deg) {
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    if (deg >= 2) {
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      return Color(0.5, 0.0, 0.5);
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    } else if (deg == 1) {
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      return Color(1.0, 0.5, 1.0);
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    } else {
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      return Color(0.0, 0.0, 0.0);
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    }
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  }
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  Graph::NodeMap<int> degree_map(graph);
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  graphToEps(graph, "graph.eps")
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    .coords(coords).scaleToA4().undirected()
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    .nodeColors(composeMap(functorMap(nodeColor), degree_map)) 
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    .run();
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\endcode 
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The \c functorMap() function makes an \c int to \c Color map from the
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\e nodeColor() function. The \c composeMap() compose the \e degree_map
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and the previous created map. The composed map is proper function to
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get color of each node.
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The usage with class type algorithms is little bit harder. In this
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case the function type map adaptors can not be used, because the
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function map adaptors give back temporarly objects.
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\code
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  Graph graph;
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  typedef Graph::EdgeMap<double> DoubleEdgeMap;
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  DoubleEdgeMap length(graph);
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  DoubleEdgeMap speed(graph);
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  typedef DivMap<DoubleEdgeMap, DoubleEdgeMap> TimeMap;
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  TimeMap time(length, speed);
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  Dijkstra<Graph, TimeMap> dijkstra(graph, time);
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  dijkstra.run(source, target);
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\endcode
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We have a length map and a maximum speed map on a graph. The minimum
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time to pass the edge can be calculated as the division of the two
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maps which can be done implicitly with the \c DivMap template
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class. We use the implicit minimum time map as the length map of the
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\c Dijkstra algorithm.
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*/
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/**
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@defgroup matrices Matrices 
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@ingroup datas
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\brief Two dimensional data storages.
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Two dimensional data storages.
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*/
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/**
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@defgroup paths Path Structures
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@ingroup datas
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\brief Path structures implemented in LEMON.
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LEMON provides flexible data structures
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to work with paths.
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All of them have similar interfaces, and it can be copied easily with
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assignment operator and copy constructor. This make it easy and
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efficient to have e.g. the Dijkstra algorithm to store its result in
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any kind of path structure.
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\sa lemon::concepts::Path
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*/
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/**
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@defgroup auxdat Auxiliary Data Structures
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@ingroup datas
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\brief Some data structures implemented in LEMON.
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This group describes the data structures implemented in LEMON in
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order to make it easier to implement combinatorial algorithms.
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*/
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/**
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@defgroup algs Algorithms
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\brief This group describes the several algorithms
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implemented in LEMON.
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This group describes the several algorithms
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implemented in LEMON.
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*/
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/**
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@defgroup search Graph Search
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@ingroup algs
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\brief This group contains the common graph
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search algorithms.
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This group contains the common graph
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search algorithms like Bfs and Dfs.
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*/
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/**
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@defgroup shortest_path Shortest Path algorithms
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@ingroup algs
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\brief This group describes the algorithms
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for finding shortest paths.
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This group describes the algorithms for finding shortest paths in
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graphs.
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*/
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/** 
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@defgroup max_flow Maximum Flow algorithms 
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@ingroup algs 
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\brief This group describes the algorithms for finding maximum flows.
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This group describes the algorithms for finding maximum flows and
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feasible circulations.
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The maximum flow problem is to find a flow between a single-source and
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single-target that is maximum. Formally, there is \f$G=(V,A)\f$
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directed graph, an \f$c_a:A\rightarrow\mathbf{R}^+_0\f$ capacity
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function and given \f$s, t \in V\f$ source and target node. The
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maximum flow is the solution of the next optimization problem:
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\f[ 0 \le f_a \le c_a \f]
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\f[ \sum_{v\in\delta^{-}(u)}f_{vu}=\sum_{v\in\delta^{+}(u)}f_{uv} \quad u \in V \setminus \{s,t\}\f]
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\f[ \max \sum_{v\in\delta^{+}(s)}f_{uv} - \sum_{v\in\delta^{-}(s)}f_{vu}\f]
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The lemon contains several algorithms for solve maximum flow problems:
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- \ref lemon::EdmondsKarp "Edmonds-Karp" 
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- \ref lemon::Preflow "Goldberg's Preflow algorithm"
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- \ref lemon::DinitzSleatorTarjan "Dinitz's blocking flow algorithm with dynamic tree"
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- \ref lemon::GoldbergTarjan "Preflow algorithm with dynamic trees"
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In most cases the \ref lemon::Preflow "preflow" algorithm provides the
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fastest method to compute the maximum flow. All impelementations
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provides functions for query the minimum cut, which is the dual linear
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programming probelm of the maximum flow.
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*/
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/**
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@defgroup min_cost_flow Minimum Cost Flow algorithms
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@ingroup algs
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\brief This group describes the algorithms
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for finding minimum cost flows and circulations.
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This group describes the algorithms for finding minimum cost flows and
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circulations.  
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*/
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/**
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@defgroup min_cut Minimum Cut algorithms 
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@ingroup algs 
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\brief This group describes the algorithms for finding minimum cut in
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graphs.
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This group describes the algorithms for finding minimum cut in graphs.
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The minimum cut problem is to find a non-empty and non-complete
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\f$X\f$ subset of the vertices with minimum overall capacity on
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outgoing arcs. Formally, there is \f$G=(V,A)\f$ directed graph, an
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\f$c_a:A\rightarrow\mathbf{R}^+_0\f$ capacity function. The minimum
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cut is the solution of the next optimization problem:
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\f[ \min_{X \subset V, X\not\in \{\emptyset, V\}}\sum_{uv\in A, u\in X, v\not\in X}c_{uv}\f]
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The lemon contains several algorithms related to minimum cut problems:
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- \ref lemon::HaoOrlin "Hao-Orlin algorithm" for calculate minimum cut
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  in directed graphs  
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- \ref lemon::NagamochiIbaraki "Nagamochi-Ibaraki algorithm" for
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  calculate minimum cut in undirected graphs
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- \ref lemon::GomoryHuTree "Gomory-Hu tree computation" for calculate all
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  pairs minimum cut in undirected graphs
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If you want to find minimum cut just between two distinict nodes,
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please see the \ref max_flow "Maximum Flow page".
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*/
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/**
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@defgroup graph_prop Connectivity and other graph properties
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@ingroup algs
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\brief This group describes the algorithms
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for discover the graph properties
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This group describes the algorithms for discover the graph properties
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like connectivity, bipartiteness, euler property, simplicity, etc...
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\image html edge_biconnected_components.png
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\image latex edge_biconnected_components.eps "bi-edge-connected components" width=\textwidth
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*/
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/**
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@defgroup planar Planarity embedding and drawing
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@ingroup algs
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\brief This group contains algorithms for planarity embedding and drawing
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This group contains algorithms for planarity checking, embedding and drawing.
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\image html planar.png
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\image latex planar.eps "Plane graph" width=\textwidth
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*/
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/**
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@defgroup matching Matching algorithms 
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@ingroup algs
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\brief This group describes the algorithms
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for find matchings in graphs and bipartite graphs.
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This group provides some algorithm objects and function to calculate
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matchings in graphs and bipartite graphs. The general matching problem is
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finding a subset of the edges which does not shares common endpoints.
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There are several different algorithms for calculate matchings in
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graphs.  The matching problems in bipartite graphs are generally
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easier than in general graphs. The goal of the matching optimization
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can be the finding maximum cardinality, maximum weight or minimum cost
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matching. The search can be constrained to find perfect or
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maximum cardinality matching.
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Lemon contains the next algorithms:
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- \ref lemon::MaxBipartiteMatching "MaxBipartiteMatching" Hopcroft-Karp 
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  augmenting path algorithm for calculate maximum cardinality matching in 
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  bipartite graphs
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- \ref lemon::PrBipartiteMatching "PrBipartiteMatching" Push-Relabel 
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  algorithm for calculate maximum cardinality matching in bipartite graphs 
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- \ref lemon::MaxWeightedBipartiteMatching "MaxWeightedBipartiteMatching" 
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  Successive shortest path algorithm for calculate maximum weighted matching 
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  and maximum weighted bipartite matching in bipartite graph
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- \ref lemon::MinCostMaxBipartiteMatching "MinCostMaxBipartiteMatching" 
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  Successive shortest path algorithm for calculate minimum cost maximum 
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  matching in bipartite graph
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- \ref lemon::MaxMatching "MaxMatching" Edmond's blossom shrinking algorithm
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  for calculate maximum cardinality matching in general graph
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- \ref lemon::MaxWeightedMatching "MaxWeightedMatching" Edmond's blossom
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  shrinking algorithm for calculate maximum weighted matching in general
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  graph
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- \ref lemon::MaxWeightedPerfectMatching "MaxWeightedPerfectMatching"
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  Edmond's blossom shrinking algorithm for calculate maximum weighted
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  perfect matching in general graph
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\image html bipartite_matching.png
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\image latex bipartite_matching.eps "Bipartite Matching" width=\textwidth
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*/
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/**
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@defgroup spantree Minimum Spanning Tree algorithms
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@ingroup algs
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\brief This group contains the algorithms for finding a minimum cost spanning
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tree in a graph
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This group contains the algorithms for finding a minimum cost spanning
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tree in a graph
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*/
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/**
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@defgroup auxalg Auxiliary algorithms
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@ingroup algs
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\brief Some algorithms implemented in LEMON.
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This group describes the algorithms in LEMON in order to make 
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it easier to implement complex algorithms.
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*/
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/**
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@defgroup approx Approximation algorithms
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\brief Approximation algorithms
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Approximation and heuristic algorithms
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*/
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/**
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@defgroup gen_opt_group General Optimization Tools
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\brief This group describes some general optimization frameworks
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implemented in LEMON.
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This group describes some general optimization frameworks
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implemented in LEMON.
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*/
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/**
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@defgroup lp_group Lp and Mip solvers
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@ingroup gen_opt_group
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\brief Lp and Mip solver interfaces for LEMON.
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This group describes Lp and Mip solver interfaces for LEMON. The
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various LP solvers could be used in the same manner with this
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interface.
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*/
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/** 
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@defgroup lp_utils Tools for Lp and Mip solvers 
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@ingroup lp_group
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\brief This group adds some helper tools to the Lp and Mip solvers
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implemented in LEMON.
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This group adds some helper tools to general optimization framework
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implemented in LEMON.
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*/
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/**
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@defgroup metah Metaheuristics
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@ingroup gen_opt_group
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\brief Metaheuristics for LEMON library.
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This group contains some metaheuristic optimization tools.
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*/
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/**
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@defgroup utils Tools and Utilities 
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\brief Tools and Utilities for Programming in LEMON
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Tools and Utilities for Programming in LEMON
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*/
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/**
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@defgroup gutils Basic Graph Utilities
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@ingroup utils
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\brief This group describes some simple basic graph utilities.
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This group describes some simple basic graph utilities.
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*/
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/**
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@defgroup misc Miscellaneous Tools
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@ingroup utils
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Here you can find several useful tools for development,
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debugging and testing.
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*/
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/**
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@defgroup timecount Time measuring and Counting
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@ingroup misc
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Here you can find simple tools for measuring the performance
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of algorithms.
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*/
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/**
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@defgroup graphbits Tools for Graph Implementation
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@ingroup utils
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\brief Tools to Make It Easier to Make Graphs.
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This group describes the tools that makes it easier to make graphs and
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the maps that dynamically update with the graph changes.
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*/
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/**
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@defgroup exceptions Exceptions
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@ingroup utils
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This group contains the exceptions thrown by LEMON library
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*/
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/**
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@defgroup io_group Input-Output
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\brief Several Graph Input-Output methods
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Here you can find tools for importing and exporting graphs 
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and graph related data. Now it supports the LEMON format, the
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\c DIMACS format and the encapsulated postscript format.
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*/
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/**
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@defgroup lemon_io Lemon Input-Output
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@ingroup io_group
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\brief Reading and writing LEMON format
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Methods for reading and writing LEMON format. More about this
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format you can find on the \ref graph-io-page "Graph Input-Output"
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tutorial pages.
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*/
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/**
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@defgroup section_io Section readers and writers
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@ingroup lemon_io
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\brief Section readers and writers for lemon Input-Output.
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Here you can find which section readers and writers can attach to
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the LemonReader and LemonWriter.
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*/
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/**
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@defgroup item_io Item Readers and Writers
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@ingroup lemon_io
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\brief Item readers and writers for lemon Input-Output.
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The Input-Output classes can handle more data type by example
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as map or attribute value. Each of these should be written and
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read some way. The module make possible to do this.  
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*/
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/**
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@defgroup eps_io Postscript exporting
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@ingroup io_group
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\brief General \c EPS drawer and graph exporter
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This group contains general \c EPS drawing methods and special
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graph exporting tools. 
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*/
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/**
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@defgroup concept Concepts
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\brief Skeleton classes and concept checking classes
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This group describes the data/algorithm skeletons and concept checking
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classes implemented in LEMON.
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The purpose of the classes in this group is fourfold.
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- These classes contain the documentations of the concepts. In order
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  to avoid document multiplications, an implementation of a concept
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  simply refers to the corresponding concept class.
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- These classes declare every functions, <tt>typedef</tt>s etc. an
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  implementation of the concepts should provide, however completely
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  without implementations and real data structures behind the
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  interface. On the other hand they should provide nothing else. All
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  the algorithms working on a data structure meeting a certain concept
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  should compile with these classes. (Though it will not run properly,
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  of course.) In this way it is easily to check if an algorithm
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  doesn't use any extra feature of a certain implementation.
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- The concept descriptor classes also provide a <em>checker class</em>
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  that makes it possible check whether a certain implementation of a
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  concept indeed provides all the required features.
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- Finally, They can serve as a skeleton of a new implementation of a concept.
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*/
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/**
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@defgroup graph_concepts Graph Structure Concepts
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@ingroup concept
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\brief Skeleton and concept checking classes for graph structures
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This group contains the skeletons and concept checking classes of LEMON's
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graph structures and helper classes used to implement these.
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*/
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/* --- Unused group
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@defgroup experimental Experimental Structures and Algorithms
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This group contains some Experimental structures and algorithms.
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The stuff here is subject to change.
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*/
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/**
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\anchor demoprograms
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@defgroup demos Demo programs
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Some demo programs are listed here. Their full source codes can be found in
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the \c demo subdirectory of the source tree.
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The standard compilation procedure (<tt>./configure;make</tt>) will compile
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them, as well. 
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*/
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/**
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@defgroup tools Standalone utility applications
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Some utility applications are listed here. 
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The standard compilation procedure (<tt>./configure;make</tt>) will compile
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them, as well. 
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*/
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