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1 #ifndef PREFLOW_PUSH_HH |
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2 #define PREFLOW_PUSH_HH |
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3 |
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4 #include <algorithm> |
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5 #include <list> |
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6 #include <vector> |
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7 //#include "pf_hiba.hh" |
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8 //#include <marci_list_graph.hh> |
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9 #include <marci_graph_traits.hh> |
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10 #include "reverse_bfs.hh" |
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11 |
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12 using namespace std; |
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13 |
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14 namespace marci { |
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15 |
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16 template <typename graph_type, typename T> |
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17 class preflow_push { |
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18 |
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19 //Hasznos typedef-ek |
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20 typedef graph_traits<graph_type>::node_iterator node_iterator; |
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21 typedef graph_traits<graph_type>::edge_iterator edge_iterator; |
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22 typedef graph_traits<graph_type>::each_node_iterator each_node_iterator; |
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23 typedef graph_traits<graph_type>::each_edge_iterator each_edge_iterator; |
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24 typedef graph_traits<graph_type>::out_edge_iterator out_edge_iterator; |
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25 typedef graph_traits<graph_type>::in_edge_iterator in_edge_iterator; |
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26 typedef graph_traits<graph_type>::sym_edge_iterator sym_edge_iterator; |
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27 |
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28 //--------------------------------------------- |
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29 //Parameters of the algorithm |
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30 //--------------------------------------------- |
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31 //Fully examine an active node until excess becomes 0 |
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32 enum node_examination_t {examine_full, examine_to_relabel}; |
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33 //No more implemented yet:, examine_only_one_edge}; |
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34 node_examination_t node_examination; |
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35 //Which implementation to be used |
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36 enum implementation_t {impl_fifo, impl_highest_label}; |
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37 //No more implemented yet:}; |
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38 implementation_t implementation; |
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39 //--------------------------------------------- |
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40 //Parameters of the algorithm |
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41 //--------------------------------------------- |
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42 |
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43 private: |
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44 //input |
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45 graph_type& G; |
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46 node_iterator s; |
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47 node_iterator t; |
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48 edge_property_vector<graph_type, T> &capacity; |
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49 //output |
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50 edge_property_vector<graph_type, T> preflow; |
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51 T maxflow_value; |
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52 |
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53 //auxiliary variables for computation |
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54 int number_of_nodes; |
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55 node_property_vector<graph_type, int> level; |
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56 node_property_vector<graph_type, T> excess; |
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57 |
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58 //Number of nodes on each level |
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59 vector<int> num_of_nodes_on_level; |
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60 |
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61 //For the FIFO implementation |
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62 list<node_iterator> fifo_nodes; |
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63 //For 'highest label' implementation |
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64 int highest_active; |
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65 //int second_highest_active; |
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66 vector< list<node_iterator> > active_nodes; |
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67 |
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68 public: |
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69 |
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70 //Constructing the object using the graph, source, sink and capacity vector |
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71 preflow_push( |
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72 graph_type& _G, |
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73 node_iterator _s, |
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74 node_iterator _t, |
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75 edge_property_vector<graph_type, T>& _capacity) |
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76 : G(_G), s(_s), t(_t), |
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77 capacity(_capacity), |
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78 preflow(_G), |
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79 //Counting the number of nodes |
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80 number_of_nodes(number_of(G.first_node())), |
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81 level(_G), |
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82 excess(_G)//, |
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83 // Default constructor: active_nodes() |
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84 { |
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85 //Simplest parameter settings |
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86 node_examination = examine_full;//examine_to_relabel;// |
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87 //Which implementation to be usedexamine_full |
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88 implementation = impl_highest_label;//impl_fifo; |
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89 |
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90 // |
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91 num_of_nodes_on_level.resize(2*number_of_nodes-1); |
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92 num_of_nodes_on_level.clear(); |
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93 |
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94 switch(implementation){ |
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95 case impl_highest_label :{ |
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96 active_nodes.resize(2*number_of_nodes-1); |
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97 active_nodes.clear(); |
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98 break; |
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99 } |
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100 default: |
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101 break; |
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102 } |
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103 |
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104 } |
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105 |
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106 //Returns the value of a maximal flow |
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107 T run(); |
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108 |
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109 edge_property_vector<graph_type, T> getmaxflow(){ |
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110 return preflow; |
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111 } |
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112 |
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113 |
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114 private: |
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115 //For testing purposes only |
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116 //Lists the node_properties |
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117 void write_property_vector(node_property_vector<graph_type, T> a, |
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118 char* prop_name="property"){ |
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119 for(each_node_iterator i=G.first_node(); i.valid(); ++i) { |
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120 cout<<"Node id.: "<<G.id(i)<<", "<<prop_name<<" value: "<<a.get(i)<<endl; |
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121 } |
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122 cout<<endl; |
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123 } |
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124 |
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125 //Modifies the excess of the node and makes sufficient changes |
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126 void modify_excess(const node_iterator& a ,T v){ |
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127 T old_value=excess.get(a); |
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128 excess.put(a,old_value+v); |
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129 } |
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130 |
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131 //This private procedure is supposed to modify the preflow on edge j |
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132 //by value v (which can be positive or negative as well) |
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133 //and maintain the excess on the head and tail |
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134 //Here we do not check whether this is possible or not |
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135 void modify_preflow(edge_iterator j, const T& v){ |
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136 |
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137 //Auxiliary variable |
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138 T old_value; |
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139 |
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140 //Modifiyng the edge |
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141 old_value=preflow.get(j); |
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142 preflow.put(j,old_value+v); |
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143 |
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144 |
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145 //Modifiyng the head |
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146 modify_excess(G.head(j),v); |
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147 |
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148 //Modifiyng the tail |
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149 modify_excess(G.tail(j),-v); |
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150 |
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151 } |
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152 |
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153 //Gives the active node to work with |
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154 //(depending on the implementation to be used) |
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155 node_iterator get_active_node(){ |
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156 //cout<<highest_active<<endl; |
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157 |
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158 switch(implementation) { |
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159 case impl_highest_label : { |
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160 |
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161 //First need to find the highest label for which there"s an active node |
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162 while( highest_active>=0 && active_nodes[highest_active].empty() ){ |
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163 --highest_active; |
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164 } |
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165 |
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166 if( highest_active>=0) { |
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167 node_iterator a=active_nodes[highest_active].front(); |
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168 active_nodes[highest_active].pop_front(); |
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169 return a; |
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170 } |
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171 else { |
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172 return node_iterator(); |
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173 } |
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174 |
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175 break; |
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176 |
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177 } |
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178 case impl_fifo : { |
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179 |
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180 if( ! fifo_nodes.empty() ) { |
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181 node_iterator a=fifo_nodes.front(); |
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182 fifo_nodes.pop_front(); |
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183 return a; |
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184 } |
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185 else { |
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186 return node_iterator(); |
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187 } |
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188 break; |
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189 } |
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190 } |
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191 // |
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192 return node_iterator(); |
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193 } |
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194 |
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195 //Puts node 'a' among the active nodes |
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196 void make_active(const node_iterator& a){ |
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197 //s and t never become active |
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198 if (a!=s && a!= t){ |
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199 switch(implementation){ |
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200 case impl_highest_label : |
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201 active_nodes[level.get(a)].push_back(a); |
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202 break; |
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203 case impl_fifo : |
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204 fifo_nodes.push_back(a); |
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205 break; |
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206 } |
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207 |
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208 } |
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209 |
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210 //Update highest_active label |
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211 if (highest_active<level.get(a)){ |
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212 highest_active=level.get(a); |
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213 } |
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214 |
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215 } |
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216 |
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217 //Changes the level of node a and make sufficent changes |
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218 void change_level_to(node_iterator a, int new_value){ |
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219 int seged = level.get(a); |
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220 level.put(a,new_value); |
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221 --num_of_nodes_on_level[seged]; |
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222 ++num_of_nodes_on_level[new_value]; |
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223 } |
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224 |
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225 //Collection of things useful (or necessary) to do before running |
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226 void preprocess(){ |
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227 |
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228 //--------------------------------------- |
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229 //Initialize parameters |
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230 //--------------------------------------- |
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231 |
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232 //Setting starting preflow, level and excess values to zero |
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233 //This can be important, if the algorithm is run more then once |
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234 for(each_node_iterator i=G.first_node(); i.valid(); ++i) { |
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235 level.put(i,0); |
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236 excess.put(i,0); |
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237 for(out_edge_iterator j=G.first_out_edge(i); j.valid(); ++j) |
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238 preflow.put(j, 0); |
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239 } |
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240 num_of_nodes_on_level[0]=number_of_nodes; |
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241 highest_active=0; |
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242 //--------------------------------------- |
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243 //Initialize parameters |
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244 //--------------------------------------- |
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245 |
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246 |
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247 //------------------------------------ |
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248 //This is the only part that uses BFS |
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249 //------------------------------------ |
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250 //Setting starting level values using reverse bfs |
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251 reverse_bfs<graph_type> rev_bfs(G,t); |
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252 rev_bfs.run(); |
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253 //write_property_vector(rev_bfs.dist,"rev_bfs"); |
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254 for(each_node_iterator i=G.first_node(); i.valid(); ++i) { |
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255 change_level_to(i,rev_bfs.dist(i)); |
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256 //level.put(i,rev_bfs.dist.get(i)); |
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257 } |
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258 //------------------------------------ |
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259 //This is the only part that uses BFS |
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260 //------------------------------------ |
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261 |
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262 |
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263 //Starting level of s |
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264 change_level_to(s,number_of_nodes); |
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265 //level.put(s,number_of_nodes); |
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266 |
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267 |
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268 //we push as much preflow from s as possible to start with |
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269 for(out_edge_iterator j=G.first_out_edge(s); j.valid(); ++j){ |
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270 modify_preflow(j,capacity.get(j) ); |
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271 make_active(G.head(j)); |
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272 int lev=level.get(G.head(j)); |
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273 if(highest_active<lev){ |
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274 highest_active=lev; |
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275 } |
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276 } |
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277 //cout<<highest_active<<endl; |
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278 } |
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279 |
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280 |
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281 //If the preflow is less than the capacity on the given edge |
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282 //then it is an edge in the residual graph |
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283 bool is_admissible_forward_edge(out_edge_iterator j, int& new_level){ |
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284 if (capacity.get(j)>preflow.get(j)){ |
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285 if(level.get(G.tail(j))==level.get(G.head(j))+1){ |
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286 return true; |
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287 } |
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288 else{ |
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289 if (level.get(G.head(j)) < new_level) |
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290 new_level=level.get(G.head(j)); |
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291 } |
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292 } |
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293 return false; |
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294 } |
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295 |
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296 //If the preflow is greater than 0 on the given edge |
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297 //then the edge reversd is an edge in the residual graph |
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298 bool is_admissible_backward_edge(in_edge_iterator j, int& new_level){ |
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299 if (0<preflow.get(j)){ |
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300 if(level.get(G.tail(j))==level.get(G.head(j))-1){ |
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301 return true; |
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302 } |
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303 else{ |
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304 if (level.get(G.tail(j)) < new_level) |
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305 new_level=level.get(G.tail(j)); |
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306 } |
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307 |
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308 } |
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309 return false; |
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310 } |
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311 |
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312 |
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313 }; //class preflow_push |
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314 |
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315 template<typename graph_type, typename T> |
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316 T preflow_push<graph_type, T>::run() { |
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317 |
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318 preprocess(); |
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319 |
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320 T e,v; |
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321 node_iterator a; |
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322 while (a=get_active_node(), a.valid()){ |
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323 //cout<<G.id(a)<<endl; |
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324 //write_property_vector(excess,"excess"); |
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325 //write_property_vector(level,"level"); |
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326 |
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327 //Initial value for the new level for the active node we are dealing with |
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328 int new_level=2*number_of_nodes; |
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329 |
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330 bool go_to_next_node=false; |
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331 e = excess.get(a); |
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332 while (!go_to_next_node){ |
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333 |
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334 //Out edges from node a |
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335 { |
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336 out_edge_iterator j=G.first_out_edge(a); |
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337 while (j.valid() && e){ |
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338 |
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339 if (is_admissible_forward_edge(j,new_level)){ |
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340 v=min(e,capacity.get(j) - preflow.get(j)); |
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341 e -= v; |
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342 //New node might become active |
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343 if (excess.get(G.head(j))==0){ |
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344 make_active(G.head(j)); |
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345 } |
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346 modify_preflow(j,v); |
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347 } |
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348 ++j; |
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349 } |
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350 } |
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351 //In edges to node a |
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352 { |
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353 in_edge_iterator j=G.first_in_edge(a); |
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354 while (j.valid() && e){ |
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355 if (is_admissible_backward_edge(j,new_level)){ |
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356 v=min(e,preflow.get(j)); |
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357 e -= v; |
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358 //New node might become active |
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359 if (excess.get(G.tail(j))==0){ |
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360 make_active(G.tail(j)); |
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361 } |
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362 modify_preflow(j,-v); |
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363 } |
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364 ++j; |
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365 } |
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366 } |
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367 |
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368 //cout<<G.id(a)<<" "<<new_level<<endl; |
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369 |
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370 if (0==e){ |
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371 //Saturating push |
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372 go_to_next_node=true; |
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373 } |
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374 else{//If there is still excess in node a |
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375 |
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376 //Level remains empty |
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377 if (num_of_nodes_on_level[level.get(a)]==1){ |
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378 change_level_to(a,number_of_nodes); |
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379 //go_to_next_node=True; |
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380 } |
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381 else{ |
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382 change_level_to(a,new_level+1); |
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383 //increase_level(a); |
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384 } |
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385 |
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386 |
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387 |
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388 |
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389 switch(node_examination){ |
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390 case examine_to_relabel: |
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391 make_active(a); |
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392 |
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393 go_to_next_node = true; |
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394 break; |
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395 default: |
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396 break; |
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397 } |
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398 |
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399 |
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400 |
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401 }//if (0==e) |
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402 } |
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403 } |
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404 maxflow_value = excess.get(t); |
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405 return maxflow_value; |
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406 }//run |
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407 |
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408 |
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409 }//namespace marci |
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410 |
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411 #endif //PREFLOW_PUSH_HH |