1 | /* -*- mode: C++; indent-tabs-mode: nil; -*- |
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2 | * |
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3 | * This file is a part of LEMON, a generic C++ optimization library. |
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4 | * |
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5 | * Copyright (C) 2003-2010 |
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6 | * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport |
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7 | * (Egervary Research Group on Combinatorial Optimization, EGRES). |
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8 | * |
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9 | * Permission to use, modify and distribute this software is granted |
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10 | * provided that this copyright notice appears in all copies. For |
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11 | * precise terms see the accompanying LICENSE file. |
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12 | * |
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13 | * This software is provided "AS IS" with no warranty of any kind, |
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14 | * express or implied, and with no claim as to its suitability for any |
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15 | * purpose. |
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16 | * |
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17 | */ |
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18 | |
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19 | namespace lemon { |
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20 | |
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21 | /** |
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22 | @defgroup datas Data Structures |
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23 | This group contains the several data structures implemented in LEMON. |
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24 | */ |
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25 | |
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26 | /** |
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27 | @defgroup graphs Graph Structures |
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28 | @ingroup datas |
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29 | \brief Graph structures implemented in LEMON. |
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30 | |
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31 | The implementation of combinatorial algorithms heavily relies on |
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32 | efficient graph implementations. LEMON offers data structures which are |
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33 | planned to be easily used in an experimental phase of implementation studies, |
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34 | and thereafter the program code can be made efficient by small modifications. |
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35 | |
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36 | The most efficient implementation of diverse applications require the |
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37 | usage of different physical graph implementations. These differences |
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38 | appear in the size of graph we require to handle, memory or time usage |
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39 | limitations or in the set of operations through which the graph can be |
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40 | accessed. LEMON provides several physical graph structures to meet |
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41 | the diverging requirements of the possible users. In order to save on |
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42 | running time or on memory usage, some structures may fail to provide |
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43 | some graph features like arc/edge or node deletion. |
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44 | |
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45 | Alteration of standard containers need a very limited number of |
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46 | operations, these together satisfy the everyday requirements. |
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47 | In the case of graph structures, different operations are needed which do |
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48 | not alter the physical graph, but gives another view. If some nodes or |
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49 | arcs have to be hidden or the reverse oriented graph have to be used, then |
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50 | this is the case. It also may happen that in a flow implementation |
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51 | the residual graph can be accessed by another algorithm, or a node-set |
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52 | is to be shrunk for another algorithm. |
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53 | LEMON also provides a variety of graphs for these requirements called |
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54 | \ref graph_adaptors "graph adaptors". Adaptors cannot be used alone but only |
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55 | in conjunction with other graph representations. |
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56 | |
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57 | You are free to use the graph structure that fit your requirements |
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58 | the best, most graph algorithms and auxiliary data structures can be used |
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59 | with any graph structure. |
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60 | |
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61 | <b>See also:</b> \ref graph_concepts "Graph Structure Concepts". |
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62 | */ |
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63 | |
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64 | /** |
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65 | @defgroup graph_adaptors Adaptor Classes for Graphs |
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66 | @ingroup graphs |
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67 | \brief Adaptor classes for digraphs and graphs |
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68 | |
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69 | This group contains several useful adaptor classes for digraphs and graphs. |
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70 | |
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71 | The main parts of LEMON are the different graph structures, generic |
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72 | graph algorithms, graph concepts, which couple them, and graph |
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73 | adaptors. While the previous notions are more or less clear, the |
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74 | latter one needs further explanation. Graph adaptors are graph classes |
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75 | which serve for considering graph structures in different ways. |
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76 | |
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77 | A short example makes this much clearer. Suppose that we have an |
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78 | instance \c g of a directed graph type, say ListDigraph and an algorithm |
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79 | \code |
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80 | template <typename Digraph> |
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81 | int algorithm(const Digraph&); |
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82 | \endcode |
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83 | is needed to run on the reverse oriented graph. It may be expensive |
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84 | (in time or in memory usage) to copy \c g with the reversed |
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85 | arcs. In this case, an adaptor class is used, which (according |
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86 | to LEMON \ref concepts::Digraph "digraph concepts") works as a digraph. |
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87 | The adaptor uses the original digraph structure and digraph operations when |
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88 | methods of the reversed oriented graph are called. This means that the adaptor |
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89 | have minor memory usage, and do not perform sophisticated algorithmic |
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90 | actions. The purpose of it is to give a tool for the cases when a |
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91 | graph have to be used in a specific alteration. If this alteration is |
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92 | obtained by a usual construction like filtering the node or the arc set or |
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93 | considering a new orientation, then an adaptor is worthwhile to use. |
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94 | To come back to the reverse oriented graph, in this situation |
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95 | \code |
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96 | template<typename Digraph> class ReverseDigraph; |
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97 | \endcode |
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98 | template class can be used. The code looks as follows |
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99 | \code |
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100 | ListDigraph g; |
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101 | ReverseDigraph<ListDigraph> rg(g); |
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102 | int result = algorithm(rg); |
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103 | \endcode |
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104 | During running the algorithm, the original digraph \c g is untouched. |
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105 | This techniques give rise to an elegant code, and based on stable |
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106 | graph adaptors, complex algorithms can be implemented easily. |
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107 | |
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108 | In flow, circulation and matching problems, the residual |
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109 | graph is of particular importance. Combining an adaptor implementing |
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110 | this with shortest path algorithms or minimum mean cycle algorithms, |
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111 | a range of weighted and cardinality optimization algorithms can be |
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112 | obtained. For other examples, the interested user is referred to the |
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113 | detailed documentation of particular adaptors. |
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114 | |
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115 | The behavior of graph adaptors can be very different. Some of them keep |
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116 | capabilities of the original graph while in other cases this would be |
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117 | meaningless. This means that the concepts that they meet depend |
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118 | on the graph adaptor, and the wrapped graph. |
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119 | For example, if an arc of a reversed digraph is deleted, this is carried |
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120 | out by deleting the corresponding arc of the original digraph, thus the |
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121 | adaptor modifies the original digraph. |
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122 | However in case of a residual digraph, this operation has no sense. |
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123 | |
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124 | Let us stand one more example here to simplify your work. |
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125 | ReverseDigraph has constructor |
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126 | \code |
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127 | ReverseDigraph(Digraph& digraph); |
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128 | \endcode |
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129 | This means that in a situation, when a <tt>const %ListDigraph&</tt> |
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130 | reference to a graph is given, then it have to be instantiated with |
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131 | <tt>Digraph=const %ListDigraph</tt>. |
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132 | \code |
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133 | int algorithm1(const ListDigraph& g) { |
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134 | ReverseDigraph<const ListDigraph> rg(g); |
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135 | return algorithm2(rg); |
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136 | } |
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137 | \endcode |
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138 | */ |
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139 | |
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140 | /** |
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141 | @defgroup maps Maps |
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142 | @ingroup datas |
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143 | \brief Map structures implemented in LEMON. |
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144 | |
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145 | This group contains the map structures implemented in LEMON. |
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146 | |
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147 | LEMON provides several special purpose maps and map adaptors that e.g. combine |
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148 | new maps from existing ones. |
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149 | |
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150 | <b>See also:</b> \ref map_concepts "Map Concepts". |
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151 | */ |
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152 | |
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153 | /** |
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154 | @defgroup graph_maps Graph Maps |
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155 | @ingroup maps |
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156 | \brief Special graph-related maps. |
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157 | |
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158 | This group contains maps that are specifically designed to assign |
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159 | values to the nodes and arcs/edges of graphs. |
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160 | |
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161 | If you are looking for the standard graph maps (\c NodeMap, \c ArcMap, |
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162 | \c EdgeMap), see the \ref graph_concepts "Graph Structure Concepts". |
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163 | */ |
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164 | |
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165 | /** |
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166 | \defgroup map_adaptors Map Adaptors |
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167 | \ingroup maps |
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168 | \brief Tools to create new maps from existing ones |
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169 | |
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170 | This group contains map adaptors that are used to create "implicit" |
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171 | maps from other maps. |
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172 | |
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173 | Most of them are \ref concepts::ReadMap "read-only maps". |
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174 | They can make arithmetic and logical operations between one or two maps |
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175 | (negation, shifting, addition, multiplication, logical 'and', 'or', |
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176 | 'not' etc.) or e.g. convert a map to another one of different Value type. |
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177 | |
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178 | The typical usage of this classes is passing implicit maps to |
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179 | algorithms. If a function type algorithm is called then the function |
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180 | type map adaptors can be used comfortable. For example let's see the |
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181 | usage of map adaptors with the \c graphToEps() function. |
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182 | \code |
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183 | Color nodeColor(int deg) { |
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184 | if (deg >= 2) { |
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185 | return Color(0.5, 0.0, 0.5); |
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186 | } else if (deg == 1) { |
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187 | return Color(1.0, 0.5, 1.0); |
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188 | } else { |
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189 | return Color(0.0, 0.0, 0.0); |
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190 | } |
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191 | } |
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192 | |
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193 | Digraph::NodeMap<int> degree_map(graph); |
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194 | |
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195 | graphToEps(graph, "graph.eps") |
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196 | .coords(coords).scaleToA4().undirected() |
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197 | .nodeColors(composeMap(functorToMap(nodeColor), degree_map)) |
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198 | .run(); |
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199 | \endcode |
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200 | The \c functorToMap() function makes an \c int to \c Color map from the |
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201 | \c nodeColor() function. The \c composeMap() compose the \c degree_map |
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202 | and the previously created map. The composed map is a proper function to |
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203 | get the color of each node. |
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204 | |
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205 | The usage with class type algorithms is little bit harder. In this |
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206 | case the function type map adaptors can not be used, because the |
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207 | function map adaptors give back temporary objects. |
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208 | \code |
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209 | Digraph graph; |
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210 | |
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211 | typedef Digraph::ArcMap<double> DoubleArcMap; |
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212 | DoubleArcMap length(graph); |
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213 | DoubleArcMap speed(graph); |
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214 | |
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215 | typedef DivMap<DoubleArcMap, DoubleArcMap> TimeMap; |
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216 | TimeMap time(length, speed); |
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217 | |
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218 | Dijkstra<Digraph, TimeMap> dijkstra(graph, time); |
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219 | dijkstra.run(source, target); |
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220 | \endcode |
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221 | We have a length map and a maximum speed map on the arcs of a digraph. |
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222 | The minimum time to pass the arc can be calculated as the division of |
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223 | the two maps which can be done implicitly with the \c DivMap template |
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224 | class. We use the implicit minimum time map as the length map of the |
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225 | \c Dijkstra algorithm. |
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226 | */ |
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227 | |
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228 | /** |
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229 | @defgroup paths Path Structures |
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230 | @ingroup datas |
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231 | \brief %Path structures implemented in LEMON. |
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232 | |
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233 | This group contains the path structures implemented in LEMON. |
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234 | |
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235 | LEMON provides flexible data structures to work with paths. |
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236 | All of them have similar interfaces and they can be copied easily with |
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237 | assignment operators and copy constructors. This makes it easy and |
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238 | efficient to have e.g. the Dijkstra algorithm to store its result in |
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239 | any kind of path structure. |
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240 | |
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241 | \sa \ref concepts::Path "Path concept" |
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242 | */ |
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243 | |
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244 | /** |
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245 | @defgroup heaps Heap Structures |
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246 | @ingroup datas |
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247 | \brief %Heap structures implemented in LEMON. |
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248 | |
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249 | This group contains the heap structures implemented in LEMON. |
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250 | |
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251 | LEMON provides several heap classes. They are efficient implementations |
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252 | of the abstract data type \e priority \e queue. They store items with |
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253 | specified values called \e priorities in such a way that finding and |
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254 | removing the item with minimum priority are efficient. |
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255 | The basic operations are adding and erasing items, changing the priority |
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256 | of an item, etc. |
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257 | |
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258 | Heaps are crucial in several algorithms, such as Dijkstra and Prim. |
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259 | The heap implementations have the same interface, thus any of them can be |
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260 | used easily in such algorithms. |
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261 | |
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262 | \sa \ref concepts::Heap "Heap concept" |
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263 | */ |
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264 | |
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265 | /** |
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266 | @defgroup auxdat Auxiliary Data Structures |
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267 | @ingroup datas |
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268 | \brief Auxiliary data structures implemented in LEMON. |
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269 | |
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270 | This group contains some data structures implemented in LEMON in |
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271 | order to make it easier to implement combinatorial algorithms. |
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272 | */ |
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273 | |
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274 | /** |
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275 | @defgroup geomdat Geometric Data Structures |
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276 | @ingroup auxdat |
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277 | \brief Geometric data structures implemented in LEMON. |
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278 | |
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279 | This group contains geometric data structures implemented in LEMON. |
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280 | |
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281 | - \ref lemon::dim2::Point "dim2::Point" implements a two dimensional |
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282 | vector with the usual operations. |
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283 | - \ref lemon::dim2::Box "dim2::Box" can be used to determine the |
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284 | rectangular bounding box of a set of \ref lemon::dim2::Point |
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285 | "dim2::Point"'s. |
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286 | */ |
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287 | |
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288 | /** |
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289 | @defgroup matrices Matrices |
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290 | @ingroup auxdat |
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291 | \brief Two dimensional data storages implemented in LEMON. |
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292 | |
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293 | This group contains two dimensional data storages implemented in LEMON. |
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294 | */ |
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295 | |
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296 | /** |
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297 | @defgroup algs Algorithms |
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298 | \brief This group contains the several algorithms |
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299 | implemented in LEMON. |
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300 | |
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301 | This group contains the several algorithms |
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302 | implemented in LEMON. |
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303 | */ |
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304 | |
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305 | /** |
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306 | @defgroup search Graph Search |
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307 | @ingroup algs |
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308 | \brief Common graph search algorithms. |
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309 | |
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310 | This group contains the common graph search algorithms, namely |
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311 | \e breadth-first \e search (BFS) and \e depth-first \e search (DFS) |
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312 | \ref clrs01algorithms. |
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313 | */ |
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314 | |
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315 | /** |
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316 | @defgroup shortest_path Shortest Path Algorithms |
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317 | @ingroup algs |
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318 | \brief Algorithms for finding shortest paths. |
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319 | |
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320 | This group contains the algorithms for finding shortest paths in digraphs |
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321 | \ref clrs01algorithms. |
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322 | |
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323 | - \ref Dijkstra algorithm for finding shortest paths from a source node |
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324 | when all arc lengths are non-negative. |
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325 | - \ref BellmanFord "Bellman-Ford" algorithm for finding shortest paths |
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326 | from a source node when arc lenghts can be either positive or negative, |
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327 | but the digraph should not contain directed cycles with negative total |
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328 | length. |
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329 | - \ref FloydWarshall "Floyd-Warshall" and \ref Johnson "Johnson" algorithms |
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330 | for solving the \e all-pairs \e shortest \e paths \e problem when arc |
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331 | lenghts can be either positive or negative, but the digraph should |
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332 | not contain directed cycles with negative total length. |
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333 | - \ref Suurballe A successive shortest path algorithm for finding |
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334 | arc-disjoint paths between two nodes having minimum total length. |
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335 | */ |
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336 | |
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337 | /** |
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338 | @defgroup spantree Minimum Spanning Tree Algorithms |
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339 | @ingroup algs |
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340 | \brief Algorithms for finding minimum cost spanning trees and arborescences. |
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341 | |
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342 | This group contains the algorithms for finding minimum cost spanning |
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343 | trees and arborescences \ref clrs01algorithms. |
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344 | */ |
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345 | |
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346 | /** |
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347 | @defgroup max_flow Maximum Flow Algorithms |
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348 | @ingroup algs |
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349 | \brief Algorithms for finding maximum flows. |
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350 | |
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351 | This group contains the algorithms for finding maximum flows and |
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352 | feasible circulations \ref clrs01algorithms, \ref amo93networkflows. |
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353 | |
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354 | The \e maximum \e flow \e problem is to find a flow of maximum value between |
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355 | a single source and a single target. Formally, there is a \f$G=(V,A)\f$ |
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356 | digraph, a \f$cap: A\rightarrow\mathbf{R}^+_0\f$ capacity function and |
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357 | \f$s, t \in V\f$ source and target nodes. |
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358 | A maximum flow is an \f$f: A\rightarrow\mathbf{R}^+_0\f$ solution of the |
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359 | following optimization problem. |
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360 | |
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361 | \f[ \max\sum_{sv\in A} f(sv) - \sum_{vs\in A} f(vs) \f] |
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362 | \f[ \sum_{uv\in A} f(uv) = \sum_{vu\in A} f(vu) |
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363 | \quad \forall u\in V\setminus\{s,t\} \f] |
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364 | \f[ 0 \leq f(uv) \leq cap(uv) \quad \forall uv\in A \f] |
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365 | |
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366 | LEMON contains several algorithms for solving maximum flow problems: |
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367 | - \ref EdmondsKarp Edmonds-Karp algorithm |
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368 | \ref edmondskarp72theoretical. |
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369 | - \ref Preflow Goldberg-Tarjan's preflow push-relabel algorithm |
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370 | \ref goldberg88newapproach. |
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371 | - \ref DinitzSleatorTarjan Dinitz's blocking flow algorithm with dynamic trees |
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372 | \ref dinic70algorithm, \ref sleator83dynamic. |
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373 | - \ref GoldbergTarjan !Preflow push-relabel algorithm with dynamic trees |
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374 | \ref goldberg88newapproach, \ref sleator83dynamic. |
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375 | |
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376 | In most cases the \ref Preflow algorithm provides the |
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377 | fastest method for computing a maximum flow. All implementations |
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378 | also provide functions to query the minimum cut, which is the dual |
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379 | problem of maximum flow. |
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380 | |
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381 | \ref Circulation is a preflow push-relabel algorithm implemented directly |
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382 | for finding feasible circulations, which is a somewhat different problem, |
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383 | but it is strongly related to maximum flow. |
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384 | For more information, see \ref Circulation. |
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385 | */ |
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386 | |
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387 | /** |
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388 | @defgroup min_cost_flow_algs Minimum Cost Flow Algorithms |
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389 | @ingroup algs |
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390 | |
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391 | \brief Algorithms for finding minimum cost flows and circulations. |
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392 | |
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393 | This group contains the algorithms for finding minimum cost flows and |
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394 | circulations \ref amo93networkflows. For more information about this |
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395 | problem and its dual solution, see \ref min_cost_flow |
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396 | "Minimum Cost Flow Problem". |
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397 | |
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398 | LEMON contains several algorithms for this problem. |
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399 | - \ref NetworkSimplex Primal Network Simplex algorithm with various |
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400 | pivot strategies \ref dantzig63linearprog, \ref kellyoneill91netsimplex. |
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401 | - \ref CostScaling Cost Scaling algorithm based on push/augment and |
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402 | relabel operations \ref goldberg90approximation, \ref goldberg97efficient, |
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403 | \ref bunnagel98efficient. |
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404 | - \ref CapacityScaling Capacity Scaling algorithm based on the successive |
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405 | shortest path method \ref edmondskarp72theoretical. |
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406 | - \ref CycleCanceling Cycle-Canceling algorithms, two of which are |
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407 | strongly polynomial \ref klein67primal, \ref goldberg89cyclecanceling. |
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408 | |
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409 | In general, \ref NetworkSimplex and \ref CostScaling are the most efficient |
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410 | implementations. |
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411 | \ref NetworkSimplex is usually the fastest on relatively small graphs (up to |
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412 | several thousands of nodes) and on dense graphs, while \ref CostScaling is |
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413 | typically more efficient on large graphs (e.g. hundreds of thousands of |
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414 | nodes or above), especially if they are sparse. |
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415 | However, other algorithms could be faster in special cases. |
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416 | For example, if the total supply and/or capacities are rather small, |
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417 | \ref CapacityScaling is usually the fastest algorithm (without effective scaling). |
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418 | |
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419 | These classes are intended to be used with integer-valued input data |
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420 | (capacities, supply values, and costs), except for \ref CapacityScaling, |
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421 | which is capable of handling real-valued arc costs (other numerical |
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422 | data are required to be integer). |
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423 | */ |
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424 | |
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425 | /** |
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426 | @defgroup min_cut Minimum Cut Algorithms |
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427 | @ingroup algs |
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428 | |
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429 | \brief Algorithms for finding minimum cut in graphs. |
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430 | |
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431 | This group contains the algorithms for finding minimum cut in graphs. |
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432 | |
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433 | The \e minimum \e cut \e problem is to find a non-empty and non-complete |
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434 | \f$X\f$ subset of the nodes with minimum overall capacity on |
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435 | outgoing arcs. Formally, there is a \f$G=(V,A)\f$ digraph, a |
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436 | \f$cap: A\rightarrow\mathbf{R}^+_0\f$ capacity function. The minimum |
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437 | cut is the \f$X\f$ solution of the next optimization problem: |
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438 | |
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439 | \f[ \min_{X \subset V, X\not\in \{\emptyset, V\}} |
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440 | \sum_{uv\in A: u\in X, v\not\in X}cap(uv) \f] |
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441 | |
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442 | LEMON contains several algorithms related to minimum cut problems: |
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443 | |
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444 | - \ref HaoOrlin "Hao-Orlin algorithm" for calculating minimum cut |
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445 | in directed graphs. |
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446 | - \ref NagamochiIbaraki "Nagamochi-Ibaraki algorithm" for |
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447 | calculating minimum cut in undirected graphs. |
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448 | - \ref GomoryHu "Gomory-Hu tree computation" for calculating |
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449 | all-pairs minimum cut in undirected graphs. |
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450 | |
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451 | If you want to find minimum cut just between two distinict nodes, |
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452 | see the \ref max_flow "maximum flow problem". |
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453 | */ |
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454 | |
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455 | /** |
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456 | @defgroup min_mean_cycle Minimum Mean Cycle Algorithms |
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457 | @ingroup algs |
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458 | \brief Algorithms for finding minimum mean cycles. |
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459 | |
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460 | This group contains the algorithms for finding minimum mean cycles |
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461 | \ref amo93networkflows, \ref karp78characterization. |
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462 | |
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463 | The \e minimum \e mean \e cycle \e problem is to find a directed cycle |
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464 | of minimum mean length (cost) in a digraph. |
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465 | The mean length of a cycle is the average length of its arcs, i.e. the |
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466 | ratio between the total length of the cycle and the number of arcs on it. |
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467 | |
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468 | This problem has an important connection to \e conservative \e length |
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469 | \e functions, too. A length function on the arcs of a digraph is called |
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470 | conservative if and only if there is no directed cycle of negative total |
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471 | length. For an arbitrary length function, the negative of the minimum |
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472 | cycle mean is the smallest \f$\epsilon\f$ value so that increasing the |
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473 | arc lengths uniformly by \f$\epsilon\f$ results in a conservative length |
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474 | function. |
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475 | |
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476 | LEMON contains three algorithms for solving the minimum mean cycle problem: |
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477 | - \ref KarpMmc Karp's original algorithm \ref karp78characterization. |
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478 | - \ref HartmannOrlinMmc Hartmann-Orlin's algorithm, which is an improved |
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479 | version of Karp's algorithm \ref hartmann93finding. |
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480 | - \ref HowardMmc Howard's policy iteration algorithm |
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481 | \ref dasdan98minmeancycle, \ref dasdan04experimental. |
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482 | |
---|
483 | In practice, the \ref HowardMmc "Howard" algorithm turned out to be by far the |
---|
484 | most efficient one, though the best known theoretical bound on its running |
---|
485 | time is exponential. |
---|
486 | Both \ref KarpMmc "Karp" and \ref HartmannOrlinMmc "Hartmann-Orlin" algorithms |
---|
487 | run in time O(ne) and use space O(n<sup>2</sup>+e), but the latter one is |
---|
488 | typically faster due to the applied early termination scheme. |
---|
489 | */ |
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490 | |
---|
491 | /** |
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492 | @defgroup matching Matching Algorithms |
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493 | @ingroup algs |
---|
494 | \brief Algorithms for finding matchings in graphs and bipartite graphs. |
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495 | |
---|
496 | This group contains the algorithms for calculating |
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497 | matchings in graphs and bipartite graphs. The general matching problem is |
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498 | finding a subset of the edges for which each node has at most one incident |
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499 | edge. |
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500 | |
---|
501 | There are several different algorithms for calculate matchings in |
---|
502 | graphs. The matching problems in bipartite graphs are generally |
---|
503 | easier than in general graphs. The goal of the matching optimization |
---|
504 | can be finding maximum cardinality, maximum weight or minimum cost |
---|
505 | matching. The search can be constrained to find perfect or |
---|
506 | maximum cardinality matching. |
---|
507 | |
---|
508 | The matching algorithms implemented in LEMON: |
---|
509 | - \ref MaxBipartiteMatching Hopcroft-Karp augmenting path algorithm |
---|
510 | for calculating maximum cardinality matching in bipartite graphs. |
---|
511 | - \ref PrBipartiteMatching Push-relabel algorithm |
---|
512 | for calculating maximum cardinality matching in bipartite graphs. |
---|
513 | - \ref MaxWeightedBipartiteMatching |
---|
514 | Successive shortest path algorithm for calculating maximum weighted |
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515 | matching and maximum weighted bipartite matching in bipartite graphs. |
---|
516 | - \ref MinCostMaxBipartiteMatching |
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517 | Successive shortest path algorithm for calculating minimum cost maximum |
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518 | matching in bipartite graphs. |
---|
519 | - \ref MaxMatching Edmond's blossom shrinking algorithm for calculating |
---|
520 | maximum cardinality matching in general graphs. |
---|
521 | - \ref MaxWeightedMatching Edmond's blossom shrinking algorithm for calculating |
---|
522 | maximum weighted matching in general graphs. |
---|
523 | - \ref MaxWeightedPerfectMatching |
---|
524 | Edmond's blossom shrinking algorithm for calculating maximum weighted |
---|
525 | perfect matching in general graphs. |
---|
526 | - \ref MaxFractionalMatching Push-relabel algorithm for calculating |
---|
527 | maximum cardinality fractional matching in general graphs. |
---|
528 | - \ref MaxWeightedFractionalMatching Augmenting path algorithm for calculating |
---|
529 | maximum weighted fractional matching in general graphs. |
---|
530 | - \ref MaxWeightedPerfectFractionalMatching |
---|
531 | Augmenting path algorithm for calculating maximum weighted |
---|
532 | perfect fractional matching in general graphs. |
---|
533 | |
---|
534 | \image html matching.png |
---|
535 | \image latex matching.eps "Min Cost Perfect Matching" width=\textwidth |
---|
536 | */ |
---|
537 | |
---|
538 | /** |
---|
539 | @defgroup graph_properties Connectivity and Other Graph Properties |
---|
540 | @ingroup algs |
---|
541 | \brief Algorithms for discovering the graph properties |
---|
542 | |
---|
543 | This group contains the algorithms for discovering the graph properties |
---|
544 | like connectivity, bipartiteness, euler property, simplicity etc. |
---|
545 | |
---|
546 | \image html connected_components.png |
---|
547 | \image latex connected_components.eps "Connected components" width=\textwidth |
---|
548 | */ |
---|
549 | |
---|
550 | /** |
---|
551 | @defgroup planar Planar Embedding and Drawing |
---|
552 | @ingroup algs |
---|
553 | \brief Algorithms for planarity checking, embedding and drawing |
---|
554 | |
---|
555 | This group contains the algorithms for planarity checking, |
---|
556 | embedding and drawing. |
---|
557 | |
---|
558 | \image html planar.png |
---|
559 | \image latex planar.eps "Plane graph" width=\textwidth |
---|
560 | */ |
---|
561 | |
---|
562 | /** |
---|
563 | @defgroup tsp Traveling Salesman Problem |
---|
564 | @ingroup algs |
---|
565 | \brief Algorithms for the symmetric traveling salesman problem |
---|
566 | |
---|
567 | This group contains basic heuristic algorithms for the the symmetric |
---|
568 | \e traveling \e salesman \e problem (TSP). |
---|
569 | Given an \ref FullGraph "undirected full graph" with a cost map on its edges, |
---|
570 | the problem is to find a shortest possible tour that visits each node exactly |
---|
571 | once (i.e. the minimum cost Hamiltonian cycle). |
---|
572 | |
---|
573 | These TSP algorithms are intended to be used with a \e metric \e cost |
---|
574 | \e function, i.e. the edge costs should satisfy the triangle inequality. |
---|
575 | Otherwise the algorithms could yield worse results. |
---|
576 | |
---|
577 | LEMON provides five well-known heuristics for solving symmetric TSP: |
---|
578 | - \ref NearestNeighborTsp Neareast neighbor algorithm |
---|
579 | - \ref GreedyTsp Greedy algorithm |
---|
580 | - \ref InsertionTsp Insertion heuristic (with four selection methods) |
---|
581 | - \ref ChristofidesTsp Christofides algorithm |
---|
582 | - \ref Opt2Tsp 2-opt algorithm |
---|
583 | |
---|
584 | \ref NearestNeighborTsp, \ref GreedyTsp, and \ref InsertionTsp are the fastest |
---|
585 | solution methods. Furthermore, \ref InsertionTsp is usually quite effective. |
---|
586 | |
---|
587 | \ref ChristofidesTsp is somewhat slower, but it has the best guaranteed |
---|
588 | approximation factor: 3/2. |
---|
589 | |
---|
590 | \ref Opt2Tsp usually provides the best results in practice, but |
---|
591 | it is the slowest method. It can also be used to improve given tours, |
---|
592 | for example, the results of other algorithms. |
---|
593 | |
---|
594 | \image html tsp.png |
---|
595 | \image latex tsp.eps "Traveling salesman problem" width=\textwidth |
---|
596 | */ |
---|
597 | |
---|
598 | /** |
---|
599 | @defgroup approx_algs Approximation Algorithms |
---|
600 | @ingroup algs |
---|
601 | \brief Approximation algorithms. |
---|
602 | |
---|
603 | This group contains the approximation and heuristic algorithms |
---|
604 | implemented in LEMON. |
---|
605 | |
---|
606 | <b>Maximum Clique Problem</b> |
---|
607 | - \ref GrossoLocatelliPullanMc An efficient heuristic algorithm of |
---|
608 | Grosso, Locatelli, and Pullan. |
---|
609 | */ |
---|
610 | |
---|
611 | /** |
---|
612 | @defgroup auxalg Auxiliary Algorithms |
---|
613 | @ingroup algs |
---|
614 | \brief Auxiliary algorithms implemented in LEMON. |
---|
615 | |
---|
616 | This group contains some algorithms implemented in LEMON |
---|
617 | in order to make it easier to implement complex algorithms. |
---|
618 | */ |
---|
619 | |
---|
620 | /** |
---|
621 | @defgroup gen_opt_group General Optimization Tools |
---|
622 | \brief This group contains some general optimization frameworks |
---|
623 | implemented in LEMON. |
---|
624 | |
---|
625 | This group contains some general optimization frameworks |
---|
626 | implemented in LEMON. |
---|
627 | */ |
---|
628 | |
---|
629 | /** |
---|
630 | @defgroup lp_group LP and MIP Solvers |
---|
631 | @ingroup gen_opt_group |
---|
632 | \brief LP and MIP solver interfaces for LEMON. |
---|
633 | |
---|
634 | This group contains LP and MIP solver interfaces for LEMON. |
---|
635 | Various LP solvers could be used in the same manner with this |
---|
636 | high-level interface. |
---|
637 | |
---|
638 | The currently supported solvers are \ref glpk, \ref clp, \ref cbc, |
---|
639 | \ref cplex, \ref soplex. |
---|
640 | */ |
---|
641 | |
---|
642 | /** |
---|
643 | @defgroup lp_utils Tools for Lp and Mip Solvers |
---|
644 | @ingroup lp_group |
---|
645 | \brief Helper tools to the Lp and Mip solvers. |
---|
646 | |
---|
647 | This group adds some helper tools to general optimization framework |
---|
648 | implemented in LEMON. |
---|
649 | */ |
---|
650 | |
---|
651 | /** |
---|
652 | @defgroup metah Metaheuristics |
---|
653 | @ingroup gen_opt_group |
---|
654 | \brief Metaheuristics for LEMON library. |
---|
655 | |
---|
656 | This group contains some metaheuristic optimization tools. |
---|
657 | */ |
---|
658 | |
---|
659 | /** |
---|
660 | @defgroup utils Tools and Utilities |
---|
661 | \brief Tools and utilities for programming in LEMON |
---|
662 | |
---|
663 | Tools and utilities for programming in LEMON. |
---|
664 | */ |
---|
665 | |
---|
666 | /** |
---|
667 | @defgroup gutils Basic Graph Utilities |
---|
668 | @ingroup utils |
---|
669 | \brief Simple basic graph utilities. |
---|
670 | |
---|
671 | This group contains some simple basic graph utilities. |
---|
672 | */ |
---|
673 | |
---|
674 | /** |
---|
675 | @defgroup misc Miscellaneous Tools |
---|
676 | @ingroup utils |
---|
677 | \brief Tools for development, debugging and testing. |
---|
678 | |
---|
679 | This group contains several useful tools for development, |
---|
680 | debugging and testing. |
---|
681 | */ |
---|
682 | |
---|
683 | /** |
---|
684 | @defgroup timecount Time Measuring and Counting |
---|
685 | @ingroup misc |
---|
686 | \brief Simple tools for measuring the performance of algorithms. |
---|
687 | |
---|
688 | This group contains simple tools for measuring the performance |
---|
689 | of algorithms. |
---|
690 | */ |
---|
691 | |
---|
692 | /** |
---|
693 | @defgroup exceptions Exceptions |
---|
694 | @ingroup utils |
---|
695 | \brief Exceptions defined in LEMON. |
---|
696 | |
---|
697 | This group contains the exceptions defined in LEMON. |
---|
698 | */ |
---|
699 | |
---|
700 | /** |
---|
701 | @defgroup io_group Input-Output |
---|
702 | \brief Graph Input-Output methods |
---|
703 | |
---|
704 | This group contains the tools for importing and exporting graphs |
---|
705 | and graph related data. Now it supports the \ref lgf-format |
---|
706 | "LEMON Graph Format", the \c DIMACS format and the encapsulated |
---|
707 | postscript (EPS) format. |
---|
708 | */ |
---|
709 | |
---|
710 | /** |
---|
711 | @defgroup lemon_io LEMON Graph Format |
---|
712 | @ingroup io_group |
---|
713 | \brief Reading and writing LEMON Graph Format. |
---|
714 | |
---|
715 | This group contains methods for reading and writing |
---|
716 | \ref lgf-format "LEMON Graph Format". |
---|
717 | */ |
---|
718 | |
---|
719 | /** |
---|
720 | @defgroup eps_io Postscript Exporting |
---|
721 | @ingroup io_group |
---|
722 | \brief General \c EPS drawer and graph exporter |
---|
723 | |
---|
724 | This group contains general \c EPS drawing methods and special |
---|
725 | graph exporting tools. |
---|
726 | */ |
---|
727 | |
---|
728 | /** |
---|
729 | @defgroup dimacs_group DIMACS Format |
---|
730 | @ingroup io_group |
---|
731 | \brief Read and write files in DIMACS format |
---|
732 | |
---|
733 | Tools to read a digraph from or write it to a file in DIMACS format data. |
---|
734 | */ |
---|
735 | |
---|
736 | /** |
---|
737 | @defgroup nauty_group NAUTY Format |
---|
738 | @ingroup io_group |
---|
739 | \brief Read \e Nauty format |
---|
740 | |
---|
741 | Tool to read graphs from \e Nauty format data. |
---|
742 | */ |
---|
743 | |
---|
744 | /** |
---|
745 | @defgroup concept Concepts |
---|
746 | \brief Skeleton classes and concept checking classes |
---|
747 | |
---|
748 | This group contains the data/algorithm skeletons and concept checking |
---|
749 | classes implemented in LEMON. |
---|
750 | |
---|
751 | The purpose of the classes in this group is fourfold. |
---|
752 | |
---|
753 | - These classes contain the documentations of the %concepts. In order |
---|
754 | to avoid document multiplications, an implementation of a concept |
---|
755 | simply refers to the corresponding concept class. |
---|
756 | |
---|
757 | - These classes declare every functions, <tt>typedef</tt>s etc. an |
---|
758 | implementation of the %concepts should provide, however completely |
---|
759 | without implementations and real data structures behind the |
---|
760 | interface. On the other hand they should provide nothing else. All |
---|
761 | the algorithms working on a data structure meeting a certain concept |
---|
762 | should compile with these classes. (Though it will not run properly, |
---|
763 | of course.) In this way it is easily to check if an algorithm |
---|
764 | doesn't use any extra feature of a certain implementation. |
---|
765 | |
---|
766 | - The concept descriptor classes also provide a <em>checker class</em> |
---|
767 | that makes it possible to check whether a certain implementation of a |
---|
768 | concept indeed provides all the required features. |
---|
769 | |
---|
770 | - Finally, They can serve as a skeleton of a new implementation of a concept. |
---|
771 | */ |
---|
772 | |
---|
773 | /** |
---|
774 | @defgroup graph_concepts Graph Structure Concepts |
---|
775 | @ingroup concept |
---|
776 | \brief Skeleton and concept checking classes for graph structures |
---|
777 | |
---|
778 | This group contains the skeletons and concept checking classes of |
---|
779 | graph structures. |
---|
780 | */ |
---|
781 | |
---|
782 | /** |
---|
783 | @defgroup map_concepts Map Concepts |
---|
784 | @ingroup concept |
---|
785 | \brief Skeleton and concept checking classes for maps |
---|
786 | |
---|
787 | This group contains the skeletons and concept checking classes of maps. |
---|
788 | */ |
---|
789 | |
---|
790 | /** |
---|
791 | @defgroup tools Standalone Utility Applications |
---|
792 | |
---|
793 | Some utility applications are listed here. |
---|
794 | |
---|
795 | The standard compilation procedure (<tt>./configure;make</tt>) will compile |
---|
796 | them, as well. |
---|
797 | */ |
---|
798 | |
---|
799 | /** |
---|
800 | \anchor demoprograms |
---|
801 | |
---|
802 | @defgroup demos Demo Programs |
---|
803 | |
---|
804 | Some demo programs are listed here. Their full source codes can be found in |
---|
805 | the \c demo subdirectory of the source tree. |
---|
806 | |
---|
807 | In order to compile them, use the <tt>make demo</tt> or the |
---|
808 | <tt>make check</tt> commands. |
---|
809 | */ |
---|
810 | |
---|
811 | } |
---|