1 | /* -*- C++ -*- |
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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) 2003-2007 |
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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 | #ifndef LEMON_DINITZ_SLEATOR_TARJAN_H |
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20 | #define LEMON_DINITZ_SLEATOR_TARJAN_H |
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21 | |
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22 | /// \file |
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23 | /// \ingroup max_flow |
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24 | /// \brief Implementation the dynamic tree data structure of Sleator |
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25 | /// and Tarjan. |
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26 | |
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27 | #include <lemon/graph_utils.h> |
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28 | #include <lemon/tolerance.h> |
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29 | #include <lemon/dynamic_tree.h> |
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30 | |
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31 | #include <vector> |
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32 | #include <limits> |
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33 | #include <fstream> |
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34 | |
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35 | |
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36 | namespace lemon { |
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37 | |
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38 | /// \brief Default traits class of DinitzSleatorTarjan class. |
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39 | /// |
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40 | /// Default traits class of DinitzSleatorTarjan class. |
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41 | /// \param _Graph Graph type. |
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42 | /// \param _CapacityMap Type of capacity map. |
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43 | template <typename _Graph, typename _CapacityMap> |
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44 | struct DinitzSleatorTarjanDefaultTraits { |
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45 | |
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46 | /// \brief The graph type the algorithm runs on. |
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47 | typedef _Graph Graph; |
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48 | |
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49 | /// \brief The type of the map that stores the edge capacities. |
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50 | /// |
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51 | /// The type of the map that stores the edge capacities. |
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52 | /// It must meet the \ref concepts::ReadMap "ReadMap" concept. |
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53 | typedef _CapacityMap CapacityMap; |
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54 | |
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55 | /// \brief The type of the length of the edges. |
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56 | typedef typename CapacityMap::Value Value; |
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57 | |
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58 | /// \brief The map type that stores the flow values. |
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59 | /// |
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60 | /// The map type that stores the flow values. |
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61 | /// It must meet the \ref concepts::ReadWriteMap "ReadWriteMap" concept. |
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62 | typedef typename Graph::template EdgeMap<Value> FlowMap; |
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63 | |
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64 | /// \brief Instantiates a FlowMap. |
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65 | /// |
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66 | /// This function instantiates a \ref FlowMap. |
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67 | /// \param graph The graph, to which we would like to define the flow map. |
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68 | static FlowMap* createFlowMap(const Graph& graph) { |
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69 | return new FlowMap(graph); |
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70 | } |
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71 | |
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72 | /// \brief The tolerance used by the algorithm |
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73 | /// |
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74 | /// The tolerance used by the algorithm to handle inexact computation. |
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75 | typedef Tolerance<Value> Tolerance; |
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76 | |
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77 | }; |
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78 | |
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79 | /// \ingroup max_flow |
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80 | /// |
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81 | /// \brief Dinitz-Sleator-Tarjan algorithms class. |
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82 | /// |
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83 | /// This class provides an implementation of the \e |
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84 | /// Dinitz-Sleator-Tarjan \e algorithm producing a flow of maximum |
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85 | /// value in a directed graph. The DinitzSleatorTarjan algorithm is |
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86 | /// the fastest known max flow algorithms wich using blocking |
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87 | /// flow. It is an improvement of the Dinitz algorithm by using the |
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88 | /// \ref DynamicTree "dynamic tree" data structure of Sleator and |
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89 | /// Tarjan. |
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90 | /// |
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91 | /// This blocking flow algorithms builds a layered graph according |
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92 | /// to \ref Bfs "breadth-first search" distance from the target node |
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93 | /// in the reversed residual graph. The layered graph contains each |
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94 | /// residual edge which steps one level down. After that the |
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95 | /// algorithm constructs a blocking flow on the layered graph and |
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96 | /// augments the overall flow with it. The number of the levels in |
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97 | /// the layered graph is strictly increasing in each augmenting |
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98 | /// phase therefore the number of the augmentings is at most |
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99 | /// \f$n-1\f$. The length of each phase is at most |
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100 | /// \f$O(m\log(n))\f$, that the overall time complexity is |
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101 | /// \f$O(nm\log(n))\f$. |
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102 | /// |
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103 | /// \param _Graph The directed graph type the algorithm runs on. |
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104 | /// \param _CapacityMap The capacity map type. |
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105 | /// \param _Traits Traits class to set various data types used by |
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106 | /// the algorithm. The default traits class is \ref |
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107 | /// DinitzSleatorTarjanDefaultTraits. See \ref |
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108 | /// DinitzSleatorTarjanDefaultTraits for the documentation of a |
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109 | /// Dinitz-Sleator-Tarjan traits class. |
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110 | /// |
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111 | /// \author Tamas Hamori and Balazs Dezso |
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112 | #ifdef DOXYGEN |
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113 | template <typename _Graph, typename _CapacityMap, typename _Traits> |
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114 | #else |
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115 | template <typename _Graph, |
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116 | typename _CapacityMap = typename _Graph::template EdgeMap<int>, |
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117 | typename _Traits = |
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118 | DinitzSleatorTarjanDefaultTraits<_Graph, _CapacityMap> > |
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119 | #endif |
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120 | class DinitzSleatorTarjan { |
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121 | public: |
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122 | |
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123 | typedef _Traits Traits; |
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124 | typedef typename Traits::Graph Graph; |
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125 | typedef typename Traits::CapacityMap CapacityMap; |
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126 | typedef typename Traits::Value Value; |
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127 | |
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128 | typedef typename Traits::FlowMap FlowMap; |
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129 | typedef typename Traits::Tolerance Tolerance; |
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130 | |
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131 | |
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132 | private: |
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133 | |
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134 | GRAPH_TYPEDEFS(typename Graph); |
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135 | |
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136 | |
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137 | typedef typename Graph::template NodeMap<int> LevelMap; |
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138 | typedef typename Graph::template NodeMap<int> IntNodeMap; |
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139 | typedef typename Graph::template NodeMap<Edge> EdgeNodeMap; |
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140 | typedef DynamicTree<Value, IntNodeMap, Tolerance, false> DynTree; |
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141 | |
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142 | private: |
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143 | |
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144 | const Graph& _graph; |
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145 | const CapacityMap* _capacity; |
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146 | |
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147 | Node _source, _target; |
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148 | |
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149 | FlowMap* _flow; |
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150 | bool _local_flow; |
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151 | |
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152 | IntNodeMap* _level; |
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153 | EdgeNodeMap* _dt_edges; |
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154 | |
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155 | IntNodeMap* _dt_index; |
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156 | DynTree* _dt; |
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157 | |
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158 | std::vector<Node> _queue; |
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159 | |
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160 | Tolerance _tolerance; |
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161 | |
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162 | Value _flow_value; |
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163 | Value _max_value; |
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164 | |
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165 | |
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166 | public: |
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167 | |
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168 | typedef DinitzSleatorTarjan Create; |
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169 | |
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170 | ///\name Named template parameters |
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171 | |
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172 | ///@{ |
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173 | |
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174 | template <typename _FlowMap> |
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175 | struct DefFlowMapTraits : public Traits { |
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176 | typedef _FlowMap FlowMap; |
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177 | static FlowMap *createFlowMap(const Graph&) { |
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178 | throw UninitializedParameter(); |
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179 | } |
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180 | }; |
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181 | |
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182 | /// \brief \ref named-templ-param "Named parameter" for setting |
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183 | /// FlowMap type |
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184 | /// |
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185 | /// \ref named-templ-param "Named parameter" for setting FlowMap |
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186 | /// type |
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187 | template <typename _FlowMap> |
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188 | struct DefFlowMap |
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189 | : public DinitzSleatorTarjan<Graph, CapacityMap, |
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190 | DefFlowMapTraits<_FlowMap> > { |
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191 | typedef DinitzSleatorTarjan<Graph, CapacityMap, |
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192 | DefFlowMapTraits<_FlowMap> > Create; |
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193 | }; |
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194 | |
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195 | template <typename _Elevator> |
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196 | struct DefElevatorTraits : public Traits { |
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197 | typedef _Elevator Elevator; |
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198 | static Elevator *createElevator(const Graph&, int) { |
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199 | throw UninitializedParameter(); |
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200 | } |
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201 | }; |
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202 | |
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203 | /// @} |
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204 | |
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205 | /// \brief \ref Exception for the case when the source equals the target. |
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206 | /// |
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207 | /// \ref Exception for the case when the source equals the target. |
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208 | /// |
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209 | class InvalidArgument : public lemon::LogicError { |
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210 | public: |
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211 | virtual const char* what() const throw() { |
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212 | return "lemon::DinitzSleatorTarjan::InvalidArgument"; |
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213 | } |
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214 | }; |
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215 | |
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216 | /// \brief The constructor of the class. |
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217 | /// |
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218 | /// The constructor of the class. |
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219 | /// \param graph The directed graph the algorithm runs on. |
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220 | /// \param capacity The capacity of the edges. |
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221 | /// \param source The source node. |
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222 | /// \param target The target node. |
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223 | DinitzSleatorTarjan(const Graph& graph, const CapacityMap& capacity, |
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224 | Node source, Node target) |
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225 | : _graph(graph), _capacity(&capacity), |
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226 | _source(source), _target(target), |
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227 | _flow(0), _local_flow(false), |
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228 | _level(0), _dt_edges(0), |
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229 | _dt_index(0), _dt(0), _queue(), |
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230 | _tolerance(), _flow_value(), _max_value() |
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231 | { |
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232 | if (_source == _target) { |
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233 | throw InvalidArgument(); |
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234 | } |
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235 | } |
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236 | |
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237 | /// \brief Destrcutor. |
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238 | /// |
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239 | /// Destructor. |
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240 | ~DinitzSleatorTarjan() { |
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241 | destroyStructures(); |
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242 | } |
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243 | |
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244 | /// \brief Sets the capacity map. |
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245 | /// |
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246 | /// Sets the capacity map. |
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247 | /// \return \c (*this) |
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248 | DinitzSleatorTarjan& capacityMap(const CapacityMap& map) { |
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249 | _capacity = ↦ |
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250 | return *this; |
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251 | } |
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252 | |
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253 | /// \brief Sets the flow map. |
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254 | /// |
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255 | /// Sets the flow map. |
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256 | /// \return \c (*this) |
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257 | DinitzSleatorTarjan& flowMap(FlowMap& map) { |
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258 | if (_local_flow) { |
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259 | delete _flow; |
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260 | _local_flow = false; |
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261 | } |
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262 | _flow = ↦ |
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263 | return *this; |
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264 | } |
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265 | |
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266 | /// \brief Returns the flow map. |
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267 | /// |
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268 | /// \return The flow map. |
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269 | const FlowMap& flowMap() { |
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270 | return *_flow; |
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271 | } |
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272 | |
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273 | /// \brief Sets the source node. |
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274 | /// |
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275 | /// Sets the source node. |
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276 | /// \return \c (*this) |
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277 | DinitzSleatorTarjan& source(const Node& node) { |
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278 | _source = node; |
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279 | return *this; |
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280 | } |
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281 | |
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282 | /// \brief Sets the target node. |
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283 | /// |
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284 | /// Sets the target node. |
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285 | /// \return \c (*this) |
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286 | DinitzSleatorTarjan& target(const Node& node) { |
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287 | _target = node; |
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288 | return *this; |
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289 | } |
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290 | |
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291 | /// \brief Sets the tolerance used by algorithm. |
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292 | /// |
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293 | /// Sets the tolerance used by algorithm. |
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294 | DinitzSleatorTarjan& tolerance(const Tolerance& tolerance) const { |
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295 | _tolerance = tolerance; |
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296 | if (_dt) { |
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297 | _dt.tolerance(_tolerance); |
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298 | } |
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299 | return *this; |
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300 | } |
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301 | |
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302 | /// \brief Returns the tolerance used by algorithm. |
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303 | /// |
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304 | /// Returns the tolerance used by algorithm. |
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305 | const Tolerance& tolerance() const { |
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306 | return tolerance; |
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307 | } |
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308 | |
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309 | private: |
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310 | |
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311 | void createStructures() { |
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312 | if (!_flow) { |
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313 | _flow = Traits::createFlowMap(_graph); |
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314 | _local_flow = true; |
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315 | } |
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316 | if (!_level) { |
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317 | _level = new LevelMap(_graph); |
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318 | } |
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319 | if (!_dt_index && !_dt) { |
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320 | _dt_index = new IntNodeMap(_graph); |
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321 | _dt = new DynTree(*_dt_index, _tolerance); |
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322 | } |
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323 | if (!_dt_edges) { |
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324 | _dt_edges = new EdgeNodeMap(_graph); |
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325 | } |
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326 | _queue.resize(countNodes(_graph)); |
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327 | _max_value = _dt->maxValue(); |
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328 | } |
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329 | |
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330 | void destroyStructures() { |
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331 | if (_local_flow) { |
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332 | delete _flow; |
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333 | } |
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334 | if (_level) { |
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335 | delete _level; |
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336 | } |
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337 | if (_dt) { |
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338 | delete _dt; |
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339 | } |
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340 | if (_dt_index) { |
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341 | delete _dt_index; |
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342 | } |
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343 | if (_dt_edges) { |
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344 | delete _dt_edges; |
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345 | } |
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346 | } |
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347 | |
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348 | bool createLayeredGraph() { |
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349 | |
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350 | for (NodeIt n(_graph); n != INVALID; ++n) { |
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351 | _level->set(n, -2); |
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352 | } |
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353 | |
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354 | int level = 0; |
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355 | |
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356 | _queue[0] = _target; |
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357 | _level->set(_target, level); |
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358 | |
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359 | int first = 0, last = 1, limit = 0; |
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360 | |
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361 | while (first != last && (*_level)[_source] == -2) { |
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362 | if (first == limit) { |
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363 | limit = last; |
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364 | ++level; |
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365 | } |
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366 | |
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367 | Node n = _queue[first++]; |
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368 | |
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369 | for (OutEdgeIt e(_graph, n); e != INVALID; ++e) { |
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370 | Node v = _graph.target(e); |
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371 | if ((*_level)[v] != -2) continue; |
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372 | Value rem = (*_flow)[e]; |
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373 | if (!_tolerance.positive(rem)) continue; |
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374 | _level->set(v, level); |
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375 | _queue[last++] = v; |
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376 | } |
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377 | |
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378 | for (InEdgeIt e(_graph, n); e != INVALID; ++e) { |
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379 | Node v = _graph.source(e); |
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380 | if ((*_level)[v] != -2) continue; |
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381 | Value rem = (*_capacity)[e] - (*_flow)[e]; |
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382 | if (!_tolerance.positive(rem)) continue; |
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383 | _level->set(v, level); |
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384 | _queue[last++] = v; |
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385 | } |
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386 | } |
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387 | return (*_level)[_source] != -2; |
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388 | } |
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389 | |
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390 | void initEdges() { |
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391 | for (NodeIt n(_graph); n != INVALID; ++n) { |
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392 | _graph.firstOut((*_dt_edges)[n], n); |
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393 | } |
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394 | } |
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395 | |
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396 | |
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397 | void augmentPath() { |
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398 | Value rem; |
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399 | Node n = _dt->findCost(_source, rem); |
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400 | _flow_value += rem; |
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401 | _dt->addCost(_source, - rem); |
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402 | |
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403 | _dt->cut(n); |
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404 | _dt->addCost(n, _max_value); |
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405 | |
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406 | Edge e = (*_dt_edges)[n]; |
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407 | if (_graph.source(e) == n) { |
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408 | _flow->set(e, (*_capacity)[e]); |
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409 | |
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410 | _graph.nextOut(e); |
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411 | if (e == INVALID) { |
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412 | _graph.firstIn(e, n); |
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413 | } |
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414 | } else { |
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415 | _flow->set(e, 0); |
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416 | _graph.nextIn(e); |
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417 | } |
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418 | _dt_edges->set(n, e); |
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419 | |
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420 | } |
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421 | |
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422 | bool advance(Node n) { |
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423 | Edge e = (*_dt_edges)[n]; |
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424 | if (e == INVALID) return false; |
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425 | |
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426 | Node u; |
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427 | Value rem; |
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428 | if (_graph.source(e) == n) { |
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429 | u = _graph.target(e); |
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430 | while ((*_level)[n] != (*_level)[u] + 1 || |
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431 | !_tolerance.positive((*_capacity)[e] - (*_flow)[e])) { |
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432 | _graph.nextOut(e); |
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433 | if (e == INVALID) break; |
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434 | u = _graph.target(e); |
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435 | } |
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436 | if (e != INVALID) { |
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437 | rem = (*_capacity)[e] - (*_flow)[e]; |
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438 | } else { |
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439 | _graph.firstIn(e, n); |
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440 | if (e == INVALID) { |
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441 | _dt_edges->set(n, INVALID); |
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442 | return false; |
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443 | } |
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444 | u = _graph.source(e); |
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445 | while ((*_level)[n] != (*_level)[u] + 1 || |
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446 | !_tolerance.positive((*_flow)[e])) { |
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447 | _graph.nextIn(e); |
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448 | if (e == INVALID) { |
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449 | _dt_edges->set(n, INVALID); |
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450 | return false; |
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451 | } |
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452 | u = _graph.source(e); |
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453 | } |
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454 | rem = (*_flow)[e]; |
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455 | } |
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456 | } else { |
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457 | u = _graph.source(e); |
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458 | while ((*_level)[n] != (*_level)[u] + 1 || |
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459 | !_tolerance.positive((*_flow)[e])) { |
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460 | _graph.nextIn(e); |
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461 | if (e == INVALID) { |
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462 | _dt_edges->set(n, INVALID); |
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463 | return false; |
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464 | } |
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465 | u = _graph.source(e); |
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466 | } |
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467 | rem = (*_flow)[e]; |
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468 | } |
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469 | |
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470 | _dt->addCost(n, - std::numeric_limits<Value>::max()); |
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471 | _dt->addCost(n, rem); |
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472 | _dt->link(n, u); |
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473 | _dt_edges->set(n, e); |
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474 | return true; |
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475 | } |
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476 | |
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477 | void retreat(Node n) { |
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478 | _level->set(n, -1); |
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479 | |
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480 | for (OutEdgeIt e(_graph, n); e != INVALID; ++e) { |
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481 | Node u = _graph.target(e); |
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482 | if ((*_dt_edges)[u] == e && _dt->findRoot(u) == n) { |
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483 | Value rem; |
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484 | _dt->findCost(u, rem); |
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485 | _flow->set(e, rem); |
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486 | _dt->cut(u); |
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487 | _dt->addCost(u, - rem); |
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488 | _dt->addCost(u, _max_value); |
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489 | } |
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490 | } |
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491 | for (InEdgeIt e(_graph, n); e != INVALID; ++e) { |
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492 | Node u = _graph.source(e); |
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493 | if ((*_dt_edges)[u] == e && _dt->findRoot(u) == n) { |
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494 | Value rem; |
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495 | _dt->findCost(u, rem); |
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496 | _flow->set(e, (*_capacity)[e] - rem); |
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497 | _dt->cut(u); |
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498 | _dt->addCost(u, - rem); |
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499 | _dt->addCost(u, _max_value); |
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500 | } |
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501 | } |
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502 | } |
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503 | |
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504 | void extractTrees() { |
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505 | for (NodeIt n(_graph); n != INVALID; ++n) { |
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506 | |
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507 | Node w = _dt->findRoot(n); |
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508 | |
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509 | while (w != n) { |
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510 | |
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511 | Value rem; |
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512 | Node u = _dt->findCost(n, rem); |
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513 | |
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514 | _dt->cut(u); |
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515 | _dt->addCost(u, - rem); |
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516 | _dt->addCost(u, _max_value); |
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517 | |
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518 | Edge e = (*_dt_edges)[u]; |
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519 | _dt_edges->set(u, INVALID); |
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520 | |
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521 | if (u == _graph.source(e)) { |
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522 | _flow->set(e, (*_capacity)[e] - rem); |
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523 | } else { |
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524 | _flow->set(e, rem); |
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525 | } |
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526 | |
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527 | w = _dt->findRoot(n); |
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528 | } |
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529 | } |
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530 | } |
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531 | |
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532 | |
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533 | public: |
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534 | |
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535 | /// \name Execution control The simplest way to execute the |
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536 | /// algorithm is to use the \c run() member functions. |
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537 | /// \n |
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538 | /// If you need more control on initial solution or |
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539 | /// execution then you have to call one \ref init() function and then |
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540 | /// the start() or multiple times the \c augment() member function. |
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541 | |
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542 | ///@{ |
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543 | |
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544 | /// \brief Initializes the algorithm |
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545 | /// |
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546 | /// It sets the flow to empty flow. |
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547 | void init() { |
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548 | createStructures(); |
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549 | |
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550 | _dt->clear(); |
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551 | for (NodeIt n(_graph); n != INVALID; ++n) { |
---|
552 | _dt->makeTree(n); |
---|
553 | _dt->addCost(n, _max_value); |
---|
554 | } |
---|
555 | |
---|
556 | for (EdgeIt it(_graph); it != INVALID; ++it) { |
---|
557 | _flow->set(it, 0); |
---|
558 | } |
---|
559 | _flow_value = 0; |
---|
560 | } |
---|
561 | |
---|
562 | /// \brief Initializes the algorithm |
---|
563 | /// |
---|
564 | /// Initializes the flow to the \c flowMap. The \c flowMap should |
---|
565 | /// contain a feasible flow, ie. in each node excluding the source |
---|
566 | /// and the target the incoming flow should be equal to the |
---|
567 | /// outgoing flow. |
---|
568 | template <typename FlowMap> |
---|
569 | void flowInit(const FlowMap& flowMap) { |
---|
570 | createStructures(); |
---|
571 | |
---|
572 | _dt->clear(); |
---|
573 | for (NodeIt n(_graph); n != INVALID; ++n) { |
---|
574 | _dt->makeTree(n); |
---|
575 | _dt->addCost(n, _max_value); |
---|
576 | } |
---|
577 | |
---|
578 | for (EdgeIt e(_graph); e != INVALID; ++e) { |
---|
579 | _flow->set(e, flowMap[e]); |
---|
580 | } |
---|
581 | _flow_value = 0; |
---|
582 | for (OutEdgeIt jt(_graph, _source); jt != INVALID; ++jt) { |
---|
583 | _flow_value += (*_flow)[jt]; |
---|
584 | } |
---|
585 | for (InEdgeIt jt(_graph, _source); jt != INVALID; ++jt) { |
---|
586 | _flow_value -= (*_flow)[jt]; |
---|
587 | } |
---|
588 | } |
---|
589 | |
---|
590 | /// \brief Initializes the algorithm |
---|
591 | /// |
---|
592 | /// Initializes the flow to the \c flowMap. The \c flowMap should |
---|
593 | /// contain a feasible flow, ie. in each node excluding the source |
---|
594 | /// and the target the incoming flow should be equal to the |
---|
595 | /// outgoing flow. |
---|
596 | /// \return %False when the given flowMap does not contain |
---|
597 | /// feasible flow. |
---|
598 | template <typename FlowMap> |
---|
599 | bool checkedFlowInit(const FlowMap& flowMap) { |
---|
600 | createStructures(); |
---|
601 | |
---|
602 | _dt->clear(); |
---|
603 | for (NodeIt n(_graph); n != INVALID; ++n) { |
---|
604 | _dt->makeTree(n); |
---|
605 | _dt->addCost(n, _max_value); |
---|
606 | } |
---|
607 | |
---|
608 | for (EdgeIt e(_graph); e != INVALID; ++e) { |
---|
609 | _flow->set(e, flowMap[e]); |
---|
610 | } |
---|
611 | for (NodeIt it(_graph); it != INVALID; ++it) { |
---|
612 | if (it == _source || it == _target) continue; |
---|
613 | Value outFlow = 0; |
---|
614 | for (OutEdgeIt jt(_graph, it); jt != INVALID; ++jt) { |
---|
615 | outFlow += (*_flow)[jt]; |
---|
616 | } |
---|
617 | Value inFlow = 0; |
---|
618 | for (InEdgeIt jt(_graph, it); jt != INVALID; ++jt) { |
---|
619 | inFlow += (*_flow)[jt]; |
---|
620 | } |
---|
621 | if (_tolerance.different(outFlow, inFlow)) { |
---|
622 | return false; |
---|
623 | } |
---|
624 | } |
---|
625 | for (EdgeIt it(_graph); it != INVALID; ++it) { |
---|
626 | if (_tolerance.less((*_flow)[it], 0)) return false; |
---|
627 | if (_tolerance.less((*_capacity)[it], (*_flow)[it])) return false; |
---|
628 | } |
---|
629 | _flow_value = 0; |
---|
630 | for (OutEdgeIt jt(_graph, _source); jt != INVALID; ++jt) { |
---|
631 | _flow_value += (*_flow)[jt]; |
---|
632 | } |
---|
633 | for (InEdgeIt jt(_graph, _source); jt != INVALID; ++jt) { |
---|
634 | _flow_value -= (*_flow)[jt]; |
---|
635 | } |
---|
636 | return true; |
---|
637 | } |
---|
638 | |
---|
639 | /// \brief Executes the algorithm |
---|
640 | /// |
---|
641 | /// It runs augmenting phases by adding blocking flow until the |
---|
642 | /// optimal solution is reached. |
---|
643 | void start() { |
---|
644 | while (augment()); |
---|
645 | } |
---|
646 | |
---|
647 | /// \brief Augments the flow with a blocking flow on a layered |
---|
648 | /// graph. |
---|
649 | /// |
---|
650 | /// This function builds a layered graph and then find a blocking |
---|
651 | /// flow on this graph. The number of the levels in the layered |
---|
652 | /// graph is strictly increasing in each augmenting phase |
---|
653 | /// therefore the number of the augmentings is at most \f$ n-1 |
---|
654 | /// \f$. The length of each phase is at most \f$ O(m \log(n)) |
---|
655 | /// \f$, that the overall time complexity is \f$ O(nm \log(n)) \f$. |
---|
656 | /// \return %False when there is not residual path between the |
---|
657 | /// source and the target so the current flow is a feasible and |
---|
658 | /// optimal solution. |
---|
659 | bool augment() { |
---|
660 | Node n; |
---|
661 | |
---|
662 | if (createLayeredGraph()) { |
---|
663 | |
---|
664 | Timer bf_timer; |
---|
665 | initEdges(); |
---|
666 | |
---|
667 | n = _dt->findRoot(_source); |
---|
668 | while (true) { |
---|
669 | Edge e; |
---|
670 | if (n == _target) { |
---|
671 | augmentPath(); |
---|
672 | } else if (!advance(n)) { |
---|
673 | if (n != _source) { |
---|
674 | retreat(n); |
---|
675 | } else { |
---|
676 | break; |
---|
677 | } |
---|
678 | } |
---|
679 | n = _dt->findRoot(_source); |
---|
680 | } |
---|
681 | extractTrees(); |
---|
682 | |
---|
683 | return true; |
---|
684 | } else { |
---|
685 | return false; |
---|
686 | } |
---|
687 | } |
---|
688 | |
---|
689 | /// \brief runs the algorithm. |
---|
690 | /// |
---|
691 | /// It is just a shorthand for: |
---|
692 | /// |
---|
693 | ///\code |
---|
694 | /// ek.init(); |
---|
695 | /// ek.start(); |
---|
696 | ///\endcode |
---|
697 | void run() { |
---|
698 | init(); |
---|
699 | start(); |
---|
700 | } |
---|
701 | |
---|
702 | /// @} |
---|
703 | |
---|
704 | /// \name Query Functions |
---|
705 | /// The result of the %Dijkstra algorithm can be obtained using these |
---|
706 | /// functions.\n |
---|
707 | /// Before the use of these functions, |
---|
708 | /// either run() or start() must be called. |
---|
709 | |
---|
710 | ///@{ |
---|
711 | |
---|
712 | /// \brief Returns the value of the maximum flow. |
---|
713 | /// |
---|
714 | /// Returns the value of the maximum flow by returning the excess |
---|
715 | /// of the target node \c t. This value equals to the value of |
---|
716 | /// the maximum flow already after the first phase. |
---|
717 | Value flowValue() const { |
---|
718 | return _flow_value; |
---|
719 | } |
---|
720 | |
---|
721 | |
---|
722 | /// \brief Returns the flow on the edge. |
---|
723 | /// |
---|
724 | /// Sets the \c flowMap to the flow on the edges. This method can |
---|
725 | /// be called after the second phase of algorithm. |
---|
726 | Value flow(const Edge& edge) const { |
---|
727 | return (*_flow)[edge]; |
---|
728 | } |
---|
729 | |
---|
730 | /// \brief Returns true when the node is on the source side of minimum cut. |
---|
731 | /// |
---|
732 | |
---|
733 | /// Returns true when the node is on the source side of minimum |
---|
734 | /// cut. This method can be called both after running \ref |
---|
735 | /// startFirstPhase() and \ref startSecondPhase(). |
---|
736 | bool minCut(const Node& node) const { |
---|
737 | return (*_level)[node] == -2; |
---|
738 | } |
---|
739 | |
---|
740 | /// \brief Returns a minimum value cut. |
---|
741 | /// |
---|
742 | /// Sets \c cut to the characteristic vector of a minimum value cut |
---|
743 | /// It simply calls the minMinCut member. |
---|
744 | /// \retval cut Write node bool map. |
---|
745 | template <typename CutMap> |
---|
746 | void minCutMap(CutMap& cutMap) const { |
---|
747 | for (NodeIt n(_graph); n != INVALID; ++n) { |
---|
748 | cutMap.set(n, (*_level)[n] == -2); |
---|
749 | } |
---|
750 | cutMap.set(_source, true); |
---|
751 | } |
---|
752 | |
---|
753 | /// @} |
---|
754 | |
---|
755 | }; |
---|
756 | } |
---|
757 | |
---|
758 | #endif |
---|