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) 2003-2008 |
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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_COST_SCALING_H |
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20 | #define LEMON_COST_SCALING_H |
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21 | |
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22 | /// \ingroup min_cost_flow_algs |
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23 | /// \file |
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24 | /// \brief Cost scaling algorithm for finding a minimum cost flow. |
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25 | |
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26 | #include <vector> |
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27 | #include <deque> |
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28 | #include <limits> |
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29 | |
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30 | #include <lemon/core.h> |
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31 | #include <lemon/maps.h> |
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32 | #include <lemon/math.h> |
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33 | #include <lemon/static_graph.h> |
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34 | #include <lemon/circulation.h> |
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35 | #include <lemon/bellman_ford.h> |
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36 | |
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37 | namespace lemon { |
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38 | |
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39 | /// \brief Default traits class of CostScaling algorithm. |
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40 | /// |
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41 | /// Default traits class of CostScaling algorithm. |
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42 | /// \tparam GR Digraph type. |
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43 | /// \tparam V The number type used for flow amounts, capacity bounds |
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44 | /// and supply values. By default it is \c int. |
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45 | /// \tparam C The number type used for costs and potentials. |
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46 | /// By default it is the same as \c V. |
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47 | #ifdef DOXYGEN |
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48 | template <typename GR, typename V = int, typename C = V> |
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49 | #else |
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50 | template < typename GR, typename V = int, typename C = V, |
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51 | bool integer = std::numeric_limits<C>::is_integer > |
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52 | #endif |
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53 | struct CostScalingDefaultTraits |
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54 | { |
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55 | /// The type of the digraph |
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56 | typedef GR Digraph; |
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57 | /// The type of the flow amounts, capacity bounds and supply values |
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58 | typedef V Value; |
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59 | /// The type of the arc costs |
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60 | typedef C Cost; |
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61 | |
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62 | /// \brief The large cost type used for internal computations |
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63 | /// |
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64 | /// The large cost type used for internal computations. |
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65 | /// It is \c long \c long if the \c Cost type is integer, |
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66 | /// otherwise it is \c double. |
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67 | /// \c Cost must be convertible to \c LargeCost. |
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68 | typedef double LargeCost; |
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69 | }; |
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70 | |
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71 | // Default traits class for integer cost types |
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72 | template <typename GR, typename V, typename C> |
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73 | struct CostScalingDefaultTraits<GR, V, C, true> |
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74 | { |
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75 | typedef GR Digraph; |
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76 | typedef V Value; |
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77 | typedef C Cost; |
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78 | #ifdef LEMON_HAVE_LONG_LONG |
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79 | typedef long long LargeCost; |
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80 | #else |
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81 | typedef long LargeCost; |
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82 | #endif |
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83 | }; |
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84 | |
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85 | |
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86 | /// \addtogroup min_cost_flow_algs |
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87 | /// @{ |
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88 | |
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89 | /// \brief Implementation of the Cost Scaling algorithm for |
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90 | /// finding a \ref min_cost_flow "minimum cost flow". |
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91 | /// |
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92 | /// \ref CostScaling implements a cost scaling algorithm that performs |
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93 | /// push/augment and relabel operations for finding a \ref min_cost_flow |
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94 | /// "minimum cost flow" \ref amo93networkflows, \ref goldberg90approximation, |
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95 | /// \ref goldberg97efficient, \ref bunnagel98efficient. |
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96 | /// It is a highly efficient primal-dual solution method, which |
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97 | /// can be viewed as the generalization of the \ref Preflow |
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98 | /// "preflow push-relabel" algorithm for the maximum flow problem. |
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99 | /// |
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100 | /// Most of the parameters of the problem (except for the digraph) |
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101 | /// can be given using separate functions, and the algorithm can be |
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102 | /// executed using the \ref run() function. If some parameters are not |
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103 | /// specified, then default values will be used. |
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104 | /// |
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105 | /// \tparam GR The digraph type the algorithm runs on. |
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106 | /// \tparam V The number type used for flow amounts, capacity bounds |
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107 | /// and supply values in the algorithm. By default, it is \c int. |
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108 | /// \tparam C The number type used for costs and potentials in the |
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109 | /// algorithm. By default, it is the same as \c V. |
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110 | /// \tparam TR The traits class that defines various types used by the |
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111 | /// algorithm. By default, it is \ref CostScalingDefaultTraits |
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112 | /// "CostScalingDefaultTraits<GR, V, C>". |
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113 | /// In most cases, this parameter should not be set directly, |
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114 | /// consider to use the named template parameters instead. |
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115 | /// |
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116 | /// \warning Both number types must be signed and all input data must |
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117 | /// be integer. |
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118 | /// \warning This algorithm does not support negative costs for such |
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119 | /// arcs that have infinite upper bound. |
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120 | /// |
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121 | /// \note %CostScaling provides three different internal methods, |
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122 | /// from which the most efficient one is used by default. |
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123 | /// For more information, see \ref Method. |
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124 | #ifdef DOXYGEN |
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125 | template <typename GR, typename V, typename C, typename TR> |
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126 | #else |
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127 | template < typename GR, typename V = int, typename C = V, |
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128 | typename TR = CostScalingDefaultTraits<GR, V, C> > |
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129 | #endif |
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130 | class CostScaling |
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131 | { |
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132 | public: |
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133 | |
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134 | /// The type of the digraph |
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135 | typedef typename TR::Digraph Digraph; |
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136 | /// The type of the flow amounts, capacity bounds and supply values |
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137 | typedef typename TR::Value Value; |
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138 | /// The type of the arc costs |
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139 | typedef typename TR::Cost Cost; |
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140 | |
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141 | /// \brief The large cost type |
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142 | /// |
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143 | /// The large cost type used for internal computations. |
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144 | /// By default, it is \c long \c long if the \c Cost type is integer, |
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145 | /// otherwise it is \c double. |
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146 | typedef typename TR::LargeCost LargeCost; |
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147 | |
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148 | /// The \ref CostScalingDefaultTraits "traits class" of the algorithm |
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149 | typedef TR Traits; |
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150 | |
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151 | public: |
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152 | |
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153 | /// \brief Problem type constants for the \c run() function. |
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154 | /// |
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155 | /// Enum type containing the problem type constants that can be |
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156 | /// returned by the \ref run() function of the algorithm. |
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157 | enum ProblemType { |
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158 | /// The problem has no feasible solution (flow). |
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159 | INFEASIBLE, |
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160 | /// The problem has optimal solution (i.e. it is feasible and |
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161 | /// bounded), and the algorithm has found optimal flow and node |
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162 | /// potentials (primal and dual solutions). |
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163 | OPTIMAL, |
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164 | /// The digraph contains an arc of negative cost and infinite |
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165 | /// upper bound. It means that the objective function is unbounded |
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166 | /// on that arc, however, note that it could actually be bounded |
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167 | /// over the feasible flows, but this algroithm cannot handle |
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168 | /// these cases. |
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169 | UNBOUNDED |
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170 | }; |
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171 | |
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172 | /// \brief Constants for selecting the internal method. |
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173 | /// |
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174 | /// Enum type containing constants for selecting the internal method |
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175 | /// for the \ref run() function. |
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176 | /// |
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177 | /// \ref CostScaling provides three internal methods that differ mainly |
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178 | /// in their base operations, which are used in conjunction with the |
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179 | /// relabel operation. |
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180 | /// By default, the so called \ref PARTIAL_AUGMENT |
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181 | /// "Partial Augment-Relabel" method is used, which proved to be |
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182 | /// the most efficient and the most robust on various test inputs. |
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183 | /// However, the other methods can be selected using the \ref run() |
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184 | /// function with the proper parameter. |
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185 | enum Method { |
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186 | /// Local push operations are used, i.e. flow is moved only on one |
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187 | /// admissible arc at once. |
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188 | PUSH, |
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189 | /// Augment operations are used, i.e. flow is moved on admissible |
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190 | /// paths from a node with excess to a node with deficit. |
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191 | AUGMENT, |
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192 | /// Partial augment operations are used, i.e. flow is moved on |
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193 | /// admissible paths started from a node with excess, but the |
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194 | /// lengths of these paths are limited. This method can be viewed |
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195 | /// as a combined version of the previous two operations. |
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196 | PARTIAL_AUGMENT |
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197 | }; |
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198 | |
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199 | private: |
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200 | |
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201 | TEMPLATE_DIGRAPH_TYPEDEFS(GR); |
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202 | |
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203 | typedef std::vector<int> IntVector; |
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204 | typedef std::vector<char> BoolVector; |
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205 | typedef std::vector<Value> ValueVector; |
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206 | typedef std::vector<Cost> CostVector; |
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207 | typedef std::vector<LargeCost> LargeCostVector; |
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208 | |
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209 | private: |
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210 | |
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211 | template <typename KT, typename VT> |
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212 | class StaticVectorMap { |
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213 | public: |
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214 | typedef KT Key; |
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215 | typedef VT Value; |
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216 | |
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217 | StaticVectorMap(std::vector<Value>& v) : _v(v) {} |
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218 | |
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219 | const Value& operator[](const Key& key) const { |
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220 | return _v[StaticDigraph::id(key)]; |
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221 | } |
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222 | |
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223 | Value& operator[](const Key& key) { |
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224 | return _v[StaticDigraph::id(key)]; |
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225 | } |
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226 | |
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227 | void set(const Key& key, const Value& val) { |
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228 | _v[StaticDigraph::id(key)] = val; |
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229 | } |
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230 | |
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231 | private: |
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232 | std::vector<Value>& _v; |
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233 | }; |
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234 | |
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235 | typedef StaticVectorMap<StaticDigraph::Node, LargeCost> LargeCostNodeMap; |
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236 | typedef StaticVectorMap<StaticDigraph::Arc, LargeCost> LargeCostArcMap; |
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237 | |
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238 | private: |
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239 | |
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240 | // Data related to the underlying digraph |
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241 | const GR &_graph; |
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242 | int _node_num; |
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243 | int _arc_num; |
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244 | int _res_node_num; |
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245 | int _res_arc_num; |
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246 | int _root; |
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247 | |
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248 | // Parameters of the problem |
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249 | bool _have_lower; |
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250 | Value _sum_supply; |
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251 | |
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252 | // Data structures for storing the digraph |
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253 | IntNodeMap _node_id; |
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254 | IntArcMap _arc_idf; |
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255 | IntArcMap _arc_idb; |
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256 | IntVector _first_out; |
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257 | BoolVector _forward; |
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258 | IntVector _source; |
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259 | IntVector _target; |
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260 | IntVector _reverse; |
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261 | |
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262 | // Node and arc data |
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263 | ValueVector _lower; |
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264 | ValueVector _upper; |
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265 | CostVector _scost; |
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266 | ValueVector _supply; |
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267 | |
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268 | ValueVector _res_cap; |
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269 | LargeCostVector _cost; |
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270 | LargeCostVector _pi; |
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271 | ValueVector _excess; |
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272 | IntVector _next_out; |
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273 | std::deque<int> _active_nodes; |
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274 | |
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275 | // Data for scaling |
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276 | LargeCost _epsilon; |
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277 | int _alpha; |
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278 | |
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279 | // Data for a StaticDigraph structure |
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280 | typedef std::pair<int, int> IntPair; |
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281 | StaticDigraph _sgr; |
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282 | std::vector<IntPair> _arc_vec; |
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283 | std::vector<LargeCost> _cost_vec; |
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284 | LargeCostArcMap _cost_map; |
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285 | LargeCostNodeMap _pi_map; |
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286 | |
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287 | public: |
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288 | |
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289 | /// \brief Constant for infinite upper bounds (capacities). |
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290 | /// |
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291 | /// Constant for infinite upper bounds (capacities). |
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292 | /// It is \c std::numeric_limits<Value>::infinity() if available, |
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293 | /// \c std::numeric_limits<Value>::max() otherwise. |
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294 | const Value INF; |
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295 | |
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296 | public: |
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297 | |
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298 | /// \name Named Template Parameters |
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299 | /// @{ |
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300 | |
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301 | template <typename T> |
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302 | struct SetLargeCostTraits : public Traits { |
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303 | typedef T LargeCost; |
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304 | }; |
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305 | |
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306 | /// \brief \ref named-templ-param "Named parameter" for setting |
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307 | /// \c LargeCost type. |
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308 | /// |
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309 | /// \ref named-templ-param "Named parameter" for setting \c LargeCost |
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310 | /// type, which is used for internal computations in the algorithm. |
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311 | /// \c Cost must be convertible to \c LargeCost. |
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312 | template <typename T> |
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313 | struct SetLargeCost |
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314 | : public CostScaling<GR, V, C, SetLargeCostTraits<T> > { |
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315 | typedef CostScaling<GR, V, C, SetLargeCostTraits<T> > Create; |
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316 | }; |
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317 | |
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318 | /// @} |
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319 | |
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320 | public: |
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321 | |
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322 | /// \brief Constructor. |
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323 | /// |
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324 | /// The constructor of the class. |
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325 | /// |
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326 | /// \param graph The digraph the algorithm runs on. |
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327 | CostScaling(const GR& graph) : |
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328 | _graph(graph), _node_id(graph), _arc_idf(graph), _arc_idb(graph), |
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329 | _cost_map(_cost_vec), _pi_map(_pi), |
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330 | INF(std::numeric_limits<Value>::has_infinity ? |
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331 | std::numeric_limits<Value>::infinity() : |
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332 | std::numeric_limits<Value>::max()) |
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333 | { |
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334 | // Check the number types |
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335 | LEMON_ASSERT(std::numeric_limits<Value>::is_signed, |
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336 | "The flow type of CostScaling must be signed"); |
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337 | LEMON_ASSERT(std::numeric_limits<Cost>::is_signed, |
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338 | "The cost type of CostScaling must be signed"); |
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339 | |
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340 | // Reset data structures |
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341 | reset(); |
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342 | } |
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343 | |
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344 | /// \name Parameters |
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345 | /// The parameters of the algorithm can be specified using these |
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346 | /// functions. |
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347 | |
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348 | /// @{ |
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349 | |
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350 | /// \brief Set the lower bounds on the arcs. |
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351 | /// |
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352 | /// This function sets the lower bounds on the arcs. |
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353 | /// If it is not used before calling \ref run(), the lower bounds |
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354 | /// will be set to zero on all arcs. |
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355 | /// |
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356 | /// \param map An arc map storing the lower bounds. |
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357 | /// Its \c Value type must be convertible to the \c Value type |
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358 | /// of the algorithm. |
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359 | /// |
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360 | /// \return <tt>(*this)</tt> |
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361 | template <typename LowerMap> |
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362 | CostScaling& lowerMap(const LowerMap& map) { |
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363 | _have_lower = true; |
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364 | for (ArcIt a(_graph); a != INVALID; ++a) { |
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365 | _lower[_arc_idf[a]] = map[a]; |
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366 | _lower[_arc_idb[a]] = map[a]; |
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367 | } |
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368 | return *this; |
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369 | } |
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370 | |
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371 | /// \brief Set the upper bounds (capacities) on the arcs. |
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372 | /// |
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373 | /// This function sets the upper bounds (capacities) on the arcs. |
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374 | /// If it is not used before calling \ref run(), the upper bounds |
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375 | /// will be set to \ref INF on all arcs (i.e. the flow value will be |
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376 | /// unbounded from above). |
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377 | /// |
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378 | /// \param map An arc map storing the upper bounds. |
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379 | /// Its \c Value type must be convertible to the \c Value type |
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380 | /// of the algorithm. |
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381 | /// |
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382 | /// \return <tt>(*this)</tt> |
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383 | template<typename UpperMap> |
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384 | CostScaling& upperMap(const UpperMap& map) { |
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385 | for (ArcIt a(_graph); a != INVALID; ++a) { |
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386 | _upper[_arc_idf[a]] = map[a]; |
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387 | } |
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388 | return *this; |
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389 | } |
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390 | |
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391 | /// \brief Set the costs of the arcs. |
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392 | /// |
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393 | /// This function sets the costs of the arcs. |
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394 | /// If it is not used before calling \ref run(), the costs |
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395 | /// will be set to \c 1 on all arcs. |
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396 | /// |
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397 | /// \param map An arc map storing the costs. |
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398 | /// Its \c Value type must be convertible to the \c Cost type |
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399 | /// of the algorithm. |
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400 | /// |
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401 | /// \return <tt>(*this)</tt> |
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402 | template<typename CostMap> |
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403 | CostScaling& costMap(const CostMap& map) { |
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404 | for (ArcIt a(_graph); a != INVALID; ++a) { |
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405 | _scost[_arc_idf[a]] = map[a]; |
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406 | _scost[_arc_idb[a]] = -map[a]; |
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407 | } |
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408 | return *this; |
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409 | } |
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410 | |
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411 | /// \brief Set the supply values of the nodes. |
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412 | /// |
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413 | /// This function sets the supply values of the nodes. |
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414 | /// If neither this function nor \ref stSupply() is used before |
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415 | /// calling \ref run(), the supply of each node will be set to zero. |
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416 | /// |
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417 | /// \param map A node map storing the supply values. |
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418 | /// Its \c Value type must be convertible to the \c Value type |
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419 | /// of the algorithm. |
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420 | /// |
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421 | /// \return <tt>(*this)</tt> |
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422 | template<typename SupplyMap> |
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423 | CostScaling& supplyMap(const SupplyMap& map) { |
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424 | for (NodeIt n(_graph); n != INVALID; ++n) { |
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425 | _supply[_node_id[n]] = map[n]; |
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426 | } |
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427 | return *this; |
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428 | } |
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429 | |
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430 | /// \brief Set single source and target nodes and a supply value. |
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431 | /// |
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432 | /// This function sets a single source node and a single target node |
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433 | /// and the required flow value. |
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434 | /// If neither this function nor \ref supplyMap() is used before |
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435 | /// calling \ref run(), the supply of each node will be set to zero. |
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436 | /// |
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437 | /// Using this function has the same effect as using \ref supplyMap() |
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438 | /// with such a map in which \c k is assigned to \c s, \c -k is |
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439 | /// assigned to \c t and all other nodes have zero supply value. |
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440 | /// |
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441 | /// \param s The source node. |
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442 | /// \param t The target node. |
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443 | /// \param k The required amount of flow from node \c s to node \c t |
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444 | /// (i.e. the supply of \c s and the demand of \c t). |
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445 | /// |
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446 | /// \return <tt>(*this)</tt> |
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447 | CostScaling& stSupply(const Node& s, const Node& t, Value k) { |
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448 | for (int i = 0; i != _res_node_num; ++i) { |
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449 | _supply[i] = 0; |
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450 | } |
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451 | _supply[_node_id[s]] = k; |
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452 | _supply[_node_id[t]] = -k; |
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453 | return *this; |
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454 | } |
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455 | |
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456 | /// @} |
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457 | |
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458 | /// \name Execution control |
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459 | /// The algorithm can be executed using \ref run(). |
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460 | |
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461 | /// @{ |
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462 | |
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463 | /// \brief Run the algorithm. |
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464 | /// |
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465 | /// This function runs the algorithm. |
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466 | /// The paramters can be specified using functions \ref lowerMap(), |
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467 | /// \ref upperMap(), \ref costMap(), \ref supplyMap(), \ref stSupply(). |
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468 | /// For example, |
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469 | /// \code |
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470 | /// CostScaling<ListDigraph> cs(graph); |
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471 | /// cs.lowerMap(lower).upperMap(upper).costMap(cost) |
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472 | /// .supplyMap(sup).run(); |
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473 | /// \endcode |
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474 | /// |
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475 | /// This function can be called more than once. All the given parameters |
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476 | /// are kept for the next call, unless \ref resetParams() or \ref reset() |
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477 | /// is used, thus only the modified parameters have to be set again. |
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478 | /// If the underlying digraph was also modified after the construction |
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479 | /// of the class (or the last \ref reset() call), then the \ref reset() |
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480 | /// function must be called. |
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481 | /// |
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482 | /// \param method The internal method that will be used in the |
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483 | /// algorithm. For more information, see \ref Method. |
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484 | /// \param factor The cost scaling factor. It must be larger than one. |
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485 | /// |
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486 | /// \return \c INFEASIBLE if no feasible flow exists, |
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487 | /// \n \c OPTIMAL if the problem has optimal solution |
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488 | /// (i.e. it is feasible and bounded), and the algorithm has found |
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489 | /// optimal flow and node potentials (primal and dual solutions), |
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490 | /// \n \c UNBOUNDED if the digraph contains an arc of negative cost |
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491 | /// and infinite upper bound. It means that the objective function |
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492 | /// is unbounded on that arc, however, note that it could actually be |
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493 | /// bounded over the feasible flows, but this algroithm cannot handle |
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494 | /// these cases. |
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495 | /// |
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496 | /// \see ProblemType, Method |
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497 | /// \see resetParams(), reset() |
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498 | ProblemType run(Method method = PARTIAL_AUGMENT, int factor = 8) { |
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499 | _alpha = factor; |
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500 | ProblemType pt = init(); |
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501 | if (pt != OPTIMAL) return pt; |
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502 | start(method); |
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503 | return OPTIMAL; |
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504 | } |
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505 | |
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506 | /// \brief Reset all the parameters that have been given before. |
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507 | /// |
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508 | /// This function resets all the paramaters that have been given |
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509 | /// before using functions \ref lowerMap(), \ref upperMap(), |
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510 | /// \ref costMap(), \ref supplyMap(), \ref stSupply(). |
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511 | /// |
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512 | /// It is useful for multiple \ref run() calls. Basically, all the given |
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513 | /// parameters are kept for the next \ref run() call, unless |
---|
514 | /// \ref resetParams() or \ref reset() is used. |
---|
515 | /// If the underlying digraph was also modified after the construction |
---|
516 | /// of the class or the last \ref reset() call, then the \ref reset() |
---|
517 | /// function must be used, otherwise \ref resetParams() is sufficient. |
---|
518 | /// |
---|
519 | /// For example, |
---|
520 | /// \code |
---|
521 | /// CostScaling<ListDigraph> cs(graph); |
---|
522 | /// |
---|
523 | /// // First run |
---|
524 | /// cs.lowerMap(lower).upperMap(upper).costMap(cost) |
---|
525 | /// .supplyMap(sup).run(); |
---|
526 | /// |
---|
527 | /// // Run again with modified cost map (resetParams() is not called, |
---|
528 | /// // so only the cost map have to be set again) |
---|
529 | /// cost[e] += 100; |
---|
530 | /// cs.costMap(cost).run(); |
---|
531 | /// |
---|
532 | /// // Run again from scratch using resetParams() |
---|
533 | /// // (the lower bounds will be set to zero on all arcs) |
---|
534 | /// cs.resetParams(); |
---|
535 | /// cs.upperMap(capacity).costMap(cost) |
---|
536 | /// .supplyMap(sup).run(); |
---|
537 | /// \endcode |
---|
538 | /// |
---|
539 | /// \return <tt>(*this)</tt> |
---|
540 | /// |
---|
541 | /// \see reset(), run() |
---|
542 | CostScaling& resetParams() { |
---|
543 | for (int i = 0; i != _res_node_num; ++i) { |
---|
544 | _supply[i] = 0; |
---|
545 | } |
---|
546 | int limit = _first_out[_root]; |
---|
547 | for (int j = 0; j != limit; ++j) { |
---|
548 | _lower[j] = 0; |
---|
549 | _upper[j] = INF; |
---|
550 | _scost[j] = _forward[j] ? 1 : -1; |
---|
551 | } |
---|
552 | for (int j = limit; j != _res_arc_num; ++j) { |
---|
553 | _lower[j] = 0; |
---|
554 | _upper[j] = INF; |
---|
555 | _scost[j] = 0; |
---|
556 | _scost[_reverse[j]] = 0; |
---|
557 | } |
---|
558 | _have_lower = false; |
---|
559 | return *this; |
---|
560 | } |
---|
561 | |
---|
562 | /// \brief Reset all the parameters that have been given before. |
---|
563 | /// |
---|
564 | /// This function resets all the paramaters that have been given |
---|
565 | /// before using functions \ref lowerMap(), \ref upperMap(), |
---|
566 | /// \ref costMap(), \ref supplyMap(), \ref stSupply(). |
---|
567 | /// |
---|
568 | /// It is useful for multiple run() calls. If this function is not |
---|
569 | /// used, all the parameters given before are kept for the next |
---|
570 | /// \ref run() call. |
---|
571 | /// However, the underlying digraph must not be modified after this |
---|
572 | /// class have been constructed, since it copies and extends the graph. |
---|
573 | /// \return <tt>(*this)</tt> |
---|
574 | CostScaling& reset() { |
---|
575 | // Resize vectors |
---|
576 | _node_num = countNodes(_graph); |
---|
577 | _arc_num = countArcs(_graph); |
---|
578 | _res_node_num = _node_num + 1; |
---|
579 | _res_arc_num = 2 * (_arc_num + _node_num); |
---|
580 | _root = _node_num; |
---|
581 | |
---|
582 | _first_out.resize(_res_node_num + 1); |
---|
583 | _forward.resize(_res_arc_num); |
---|
584 | _source.resize(_res_arc_num); |
---|
585 | _target.resize(_res_arc_num); |
---|
586 | _reverse.resize(_res_arc_num); |
---|
587 | |
---|
588 | _lower.resize(_res_arc_num); |
---|
589 | _upper.resize(_res_arc_num); |
---|
590 | _scost.resize(_res_arc_num); |
---|
591 | _supply.resize(_res_node_num); |
---|
592 | |
---|
593 | _res_cap.resize(_res_arc_num); |
---|
594 | _cost.resize(_res_arc_num); |
---|
595 | _pi.resize(_res_node_num); |
---|
596 | _excess.resize(_res_node_num); |
---|
597 | _next_out.resize(_res_node_num); |
---|
598 | |
---|
599 | _arc_vec.reserve(_res_arc_num); |
---|
600 | _cost_vec.reserve(_res_arc_num); |
---|
601 | |
---|
602 | // Copy the graph |
---|
603 | int i = 0, j = 0, k = 2 * _arc_num + _node_num; |
---|
604 | for (NodeIt n(_graph); n != INVALID; ++n, ++i) { |
---|
605 | _node_id[n] = i; |
---|
606 | } |
---|
607 | i = 0; |
---|
608 | for (NodeIt n(_graph); n != INVALID; ++n, ++i) { |
---|
609 | _first_out[i] = j; |
---|
610 | for (OutArcIt a(_graph, n); a != INVALID; ++a, ++j) { |
---|
611 | _arc_idf[a] = j; |
---|
612 | _forward[j] = true; |
---|
613 | _source[j] = i; |
---|
614 | _target[j] = _node_id[_graph.runningNode(a)]; |
---|
615 | } |
---|
616 | for (InArcIt a(_graph, n); a != INVALID; ++a, ++j) { |
---|
617 | _arc_idb[a] = j; |
---|
618 | _forward[j] = false; |
---|
619 | _source[j] = i; |
---|
620 | _target[j] = _node_id[_graph.runningNode(a)]; |
---|
621 | } |
---|
622 | _forward[j] = false; |
---|
623 | _source[j] = i; |
---|
624 | _target[j] = _root; |
---|
625 | _reverse[j] = k; |
---|
626 | _forward[k] = true; |
---|
627 | _source[k] = _root; |
---|
628 | _target[k] = i; |
---|
629 | _reverse[k] = j; |
---|
630 | ++j; ++k; |
---|
631 | } |
---|
632 | _first_out[i] = j; |
---|
633 | _first_out[_res_node_num] = k; |
---|
634 | for (ArcIt a(_graph); a != INVALID; ++a) { |
---|
635 | int fi = _arc_idf[a]; |
---|
636 | int bi = _arc_idb[a]; |
---|
637 | _reverse[fi] = bi; |
---|
638 | _reverse[bi] = fi; |
---|
639 | } |
---|
640 | |
---|
641 | // Reset parameters |
---|
642 | resetParams(); |
---|
643 | return *this; |
---|
644 | } |
---|
645 | |
---|
646 | /// @} |
---|
647 | |
---|
648 | /// \name Query Functions |
---|
649 | /// The results of the algorithm can be obtained using these |
---|
650 | /// functions.\n |
---|
651 | /// The \ref run() function must be called before using them. |
---|
652 | |
---|
653 | /// @{ |
---|
654 | |
---|
655 | /// \brief Return the total cost of the found flow. |
---|
656 | /// |
---|
657 | /// This function returns the total cost of the found flow. |
---|
658 | /// Its complexity is O(e). |
---|
659 | /// |
---|
660 | /// \note The return type of the function can be specified as a |
---|
661 | /// template parameter. For example, |
---|
662 | /// \code |
---|
663 | /// cs.totalCost<double>(); |
---|
664 | /// \endcode |
---|
665 | /// It is useful if the total cost cannot be stored in the \c Cost |
---|
666 | /// type of the algorithm, which is the default return type of the |
---|
667 | /// function. |
---|
668 | /// |
---|
669 | /// \pre \ref run() must be called before using this function. |
---|
670 | template <typename Number> |
---|
671 | Number totalCost() const { |
---|
672 | Number c = 0; |
---|
673 | for (ArcIt a(_graph); a != INVALID; ++a) { |
---|
674 | int i = _arc_idb[a]; |
---|
675 | c += static_cast<Number>(_res_cap[i]) * |
---|
676 | (-static_cast<Number>(_scost[i])); |
---|
677 | } |
---|
678 | return c; |
---|
679 | } |
---|
680 | |
---|
681 | #ifndef DOXYGEN |
---|
682 | Cost totalCost() const { |
---|
683 | return totalCost<Cost>(); |
---|
684 | } |
---|
685 | #endif |
---|
686 | |
---|
687 | /// \brief Return the flow on the given arc. |
---|
688 | /// |
---|
689 | /// This function returns the flow on the given arc. |
---|
690 | /// |
---|
691 | /// \pre \ref run() must be called before using this function. |
---|
692 | Value flow(const Arc& a) const { |
---|
693 | return _res_cap[_arc_idb[a]]; |
---|
694 | } |
---|
695 | |
---|
696 | /// \brief Return the flow map (the primal solution). |
---|
697 | /// |
---|
698 | /// This function copies the flow value on each arc into the given |
---|
699 | /// map. The \c Value type of the algorithm must be convertible to |
---|
700 | /// the \c Value type of the map. |
---|
701 | /// |
---|
702 | /// \pre \ref run() must be called before using this function. |
---|
703 | template <typename FlowMap> |
---|
704 | void flowMap(FlowMap &map) const { |
---|
705 | for (ArcIt a(_graph); a != INVALID; ++a) { |
---|
706 | map.set(a, _res_cap[_arc_idb[a]]); |
---|
707 | } |
---|
708 | } |
---|
709 | |
---|
710 | /// \brief Return the potential (dual value) of the given node. |
---|
711 | /// |
---|
712 | /// This function returns the potential (dual value) of the |
---|
713 | /// given node. |
---|
714 | /// |
---|
715 | /// \pre \ref run() must be called before using this function. |
---|
716 | Cost potential(const Node& n) const { |
---|
717 | return static_cast<Cost>(_pi[_node_id[n]]); |
---|
718 | } |
---|
719 | |
---|
720 | /// \brief Return the potential map (the dual solution). |
---|
721 | /// |
---|
722 | /// This function copies the potential (dual value) of each node |
---|
723 | /// into the given map. |
---|
724 | /// The \c Cost type of the algorithm must be convertible to the |
---|
725 | /// \c Value type of the map. |
---|
726 | /// |
---|
727 | /// \pre \ref run() must be called before using this function. |
---|
728 | template <typename PotentialMap> |
---|
729 | void potentialMap(PotentialMap &map) const { |
---|
730 | for (NodeIt n(_graph); n != INVALID; ++n) { |
---|
731 | map.set(n, static_cast<Cost>(_pi[_node_id[n]])); |
---|
732 | } |
---|
733 | } |
---|
734 | |
---|
735 | /// @} |
---|
736 | |
---|
737 | private: |
---|
738 | |
---|
739 | // Initialize the algorithm |
---|
740 | ProblemType init() { |
---|
741 | if (_res_node_num <= 1) return INFEASIBLE; |
---|
742 | |
---|
743 | // Check the sum of supply values |
---|
744 | _sum_supply = 0; |
---|
745 | for (int i = 0; i != _root; ++i) { |
---|
746 | _sum_supply += _supply[i]; |
---|
747 | } |
---|
748 | if (_sum_supply > 0) return INFEASIBLE; |
---|
749 | |
---|
750 | |
---|
751 | // Initialize vectors |
---|
752 | for (int i = 0; i != _res_node_num; ++i) { |
---|
753 | _pi[i] = 0; |
---|
754 | _excess[i] = _supply[i]; |
---|
755 | } |
---|
756 | |
---|
757 | // Remove infinite upper bounds and check negative arcs |
---|
758 | const Value MAX = std::numeric_limits<Value>::max(); |
---|
759 | int last_out; |
---|
760 | if (_have_lower) { |
---|
761 | for (int i = 0; i != _root; ++i) { |
---|
762 | last_out = _first_out[i+1]; |
---|
763 | for (int j = _first_out[i]; j != last_out; ++j) { |
---|
764 | if (_forward[j]) { |
---|
765 | Value c = _scost[j] < 0 ? _upper[j] : _lower[j]; |
---|
766 | if (c >= MAX) return UNBOUNDED; |
---|
767 | _excess[i] -= c; |
---|
768 | _excess[_target[j]] += c; |
---|
769 | } |
---|
770 | } |
---|
771 | } |
---|
772 | } else { |
---|
773 | for (int i = 0; i != _root; ++i) { |
---|
774 | last_out = _first_out[i+1]; |
---|
775 | for (int j = _first_out[i]; j != last_out; ++j) { |
---|
776 | if (_forward[j] && _scost[j] < 0) { |
---|
777 | Value c = _upper[j]; |
---|
778 | if (c >= MAX) return UNBOUNDED; |
---|
779 | _excess[i] -= c; |
---|
780 | _excess[_target[j]] += c; |
---|
781 | } |
---|
782 | } |
---|
783 | } |
---|
784 | } |
---|
785 | Value ex, max_cap = 0; |
---|
786 | for (int i = 0; i != _res_node_num; ++i) { |
---|
787 | ex = _excess[i]; |
---|
788 | _excess[i] = 0; |
---|
789 | if (ex < 0) max_cap -= ex; |
---|
790 | } |
---|
791 | for (int j = 0; j != _res_arc_num; ++j) { |
---|
792 | if (_upper[j] >= MAX) _upper[j] = max_cap; |
---|
793 | } |
---|
794 | |
---|
795 | // Initialize the large cost vector and the epsilon parameter |
---|
796 | _epsilon = 0; |
---|
797 | LargeCost lc; |
---|
798 | for (int i = 0; i != _root; ++i) { |
---|
799 | last_out = _first_out[i+1]; |
---|
800 | for (int j = _first_out[i]; j != last_out; ++j) { |
---|
801 | lc = static_cast<LargeCost>(_scost[j]) * _res_node_num * _alpha; |
---|
802 | _cost[j] = lc; |
---|
803 | if (lc > _epsilon) _epsilon = lc; |
---|
804 | } |
---|
805 | } |
---|
806 | _epsilon /= _alpha; |
---|
807 | |
---|
808 | // Initialize maps for Circulation and remove non-zero lower bounds |
---|
809 | ConstMap<Arc, Value> low(0); |
---|
810 | typedef typename Digraph::template ArcMap<Value> ValueArcMap; |
---|
811 | typedef typename Digraph::template NodeMap<Value> ValueNodeMap; |
---|
812 | ValueArcMap cap(_graph), flow(_graph); |
---|
813 | ValueNodeMap sup(_graph); |
---|
814 | for (NodeIt n(_graph); n != INVALID; ++n) { |
---|
815 | sup[n] = _supply[_node_id[n]]; |
---|
816 | } |
---|
817 | if (_have_lower) { |
---|
818 | for (ArcIt a(_graph); a != INVALID; ++a) { |
---|
819 | int j = _arc_idf[a]; |
---|
820 | Value c = _lower[j]; |
---|
821 | cap[a] = _upper[j] - c; |
---|
822 | sup[_graph.source(a)] -= c; |
---|
823 | sup[_graph.target(a)] += c; |
---|
824 | } |
---|
825 | } else { |
---|
826 | for (ArcIt a(_graph); a != INVALID; ++a) { |
---|
827 | cap[a] = _upper[_arc_idf[a]]; |
---|
828 | } |
---|
829 | } |
---|
830 | |
---|
831 | // Find a feasible flow using Circulation |
---|
832 | Circulation<Digraph, ConstMap<Arc, Value>, ValueArcMap, ValueNodeMap> |
---|
833 | circ(_graph, low, cap, sup); |
---|
834 | if (!circ.flowMap(flow).run()) return INFEASIBLE; |
---|
835 | |
---|
836 | // Set residual capacities and handle GEQ supply type |
---|
837 | if (_sum_supply < 0) { |
---|
838 | for (ArcIt a(_graph); a != INVALID; ++a) { |
---|
839 | Value fa = flow[a]; |
---|
840 | _res_cap[_arc_idf[a]] = cap[a] - fa; |
---|
841 | _res_cap[_arc_idb[a]] = fa; |
---|
842 | sup[_graph.source(a)] -= fa; |
---|
843 | sup[_graph.target(a)] += fa; |
---|
844 | } |
---|
845 | for (NodeIt n(_graph); n != INVALID; ++n) { |
---|
846 | _excess[_node_id[n]] = sup[n]; |
---|
847 | } |
---|
848 | for (int a = _first_out[_root]; a != _res_arc_num; ++a) { |
---|
849 | int u = _target[a]; |
---|
850 | int ra = _reverse[a]; |
---|
851 | _res_cap[a] = -_sum_supply + 1; |
---|
852 | _res_cap[ra] = -_excess[u]; |
---|
853 | _cost[a] = 0; |
---|
854 | _cost[ra] = 0; |
---|
855 | _excess[u] = 0; |
---|
856 | } |
---|
857 | } else { |
---|
858 | for (ArcIt a(_graph); a != INVALID; ++a) { |
---|
859 | Value fa = flow[a]; |
---|
860 | _res_cap[_arc_idf[a]] = cap[a] - fa; |
---|
861 | _res_cap[_arc_idb[a]] = fa; |
---|
862 | } |
---|
863 | for (int a = _first_out[_root]; a != _res_arc_num; ++a) { |
---|
864 | int ra = _reverse[a]; |
---|
865 | _res_cap[a] = 1; |
---|
866 | _res_cap[ra] = 0; |
---|
867 | _cost[a] = 0; |
---|
868 | _cost[ra] = 0; |
---|
869 | } |
---|
870 | } |
---|
871 | |
---|
872 | return OPTIMAL; |
---|
873 | } |
---|
874 | |
---|
875 | // Execute the algorithm and transform the results |
---|
876 | void start(Method method) { |
---|
877 | // Maximum path length for partial augment |
---|
878 | const int MAX_PATH_LENGTH = 4; |
---|
879 | |
---|
880 | // Execute the algorithm |
---|
881 | switch (method) { |
---|
882 | case PUSH: |
---|
883 | startPush(); |
---|
884 | break; |
---|
885 | case AUGMENT: |
---|
886 | startAugment(); |
---|
887 | break; |
---|
888 | case PARTIAL_AUGMENT: |
---|
889 | startAugment(MAX_PATH_LENGTH); |
---|
890 | break; |
---|
891 | } |
---|
892 | |
---|
893 | // Compute node potentials for the original costs |
---|
894 | _arc_vec.clear(); |
---|
895 | _cost_vec.clear(); |
---|
896 | for (int j = 0; j != _res_arc_num; ++j) { |
---|
897 | if (_res_cap[j] > 0) { |
---|
898 | _arc_vec.push_back(IntPair(_source[j], _target[j])); |
---|
899 | _cost_vec.push_back(_scost[j]); |
---|
900 | } |
---|
901 | } |
---|
902 | _sgr.build(_res_node_num, _arc_vec.begin(), _arc_vec.end()); |
---|
903 | |
---|
904 | typename BellmanFord<StaticDigraph, LargeCostArcMap> |
---|
905 | ::template SetDistMap<LargeCostNodeMap>::Create bf(_sgr, _cost_map); |
---|
906 | bf.distMap(_pi_map); |
---|
907 | bf.init(0); |
---|
908 | bf.start(); |
---|
909 | |
---|
910 | // Handle non-zero lower bounds |
---|
911 | if (_have_lower) { |
---|
912 | int limit = _first_out[_root]; |
---|
913 | for (int j = 0; j != limit; ++j) { |
---|
914 | if (!_forward[j]) _res_cap[j] += _lower[j]; |
---|
915 | } |
---|
916 | } |
---|
917 | } |
---|
918 | |
---|
919 | /// Execute the algorithm performing augment and relabel operations |
---|
920 | void startAugment(int max_length = std::numeric_limits<int>::max()) { |
---|
921 | // Paramters for heuristics |
---|
922 | const int BF_HEURISTIC_EPSILON_BOUND = 1000; |
---|
923 | const int BF_HEURISTIC_BOUND_FACTOR = 3; |
---|
924 | |
---|
925 | // Perform cost scaling phases |
---|
926 | IntVector pred_arc(_res_node_num); |
---|
927 | std::vector<int> path_nodes; |
---|
928 | for ( ; _epsilon >= 1; _epsilon = _epsilon < _alpha && _epsilon > 1 ? |
---|
929 | 1 : _epsilon / _alpha ) |
---|
930 | { |
---|
931 | // "Early Termination" heuristic: use Bellman-Ford algorithm |
---|
932 | // to check if the current flow is optimal |
---|
933 | if (_epsilon <= BF_HEURISTIC_EPSILON_BOUND) { |
---|
934 | _arc_vec.clear(); |
---|
935 | _cost_vec.clear(); |
---|
936 | for (int j = 0; j != _res_arc_num; ++j) { |
---|
937 | if (_res_cap[j] > 0) { |
---|
938 | _arc_vec.push_back(IntPair(_source[j], _target[j])); |
---|
939 | _cost_vec.push_back(_cost[j] + 1); |
---|
940 | } |
---|
941 | } |
---|
942 | _sgr.build(_res_node_num, _arc_vec.begin(), _arc_vec.end()); |
---|
943 | |
---|
944 | BellmanFord<StaticDigraph, LargeCostArcMap> bf(_sgr, _cost_map); |
---|
945 | bf.init(0); |
---|
946 | bool done = false; |
---|
947 | int K = int(BF_HEURISTIC_BOUND_FACTOR * sqrt(_res_node_num)); |
---|
948 | for (int i = 0; i < K && !done; ++i) |
---|
949 | done = bf.processNextWeakRound(); |
---|
950 | if (done) break; |
---|
951 | } |
---|
952 | |
---|
953 | // Saturate arcs not satisfying the optimality condition |
---|
954 | for (int a = 0; a != _res_arc_num; ++a) { |
---|
955 | if (_res_cap[a] > 0 && |
---|
956 | _cost[a] + _pi[_source[a]] - _pi[_target[a]] < 0) { |
---|
957 | Value delta = _res_cap[a]; |
---|
958 | _excess[_source[a]] -= delta; |
---|
959 | _excess[_target[a]] += delta; |
---|
960 | _res_cap[a] = 0; |
---|
961 | _res_cap[_reverse[a]] += delta; |
---|
962 | } |
---|
963 | } |
---|
964 | |
---|
965 | // Find active nodes (i.e. nodes with positive excess) |
---|
966 | for (int u = 0; u != _res_node_num; ++u) { |
---|
967 | if (_excess[u] > 0) _active_nodes.push_back(u); |
---|
968 | } |
---|
969 | |
---|
970 | // Initialize the next arcs |
---|
971 | for (int u = 0; u != _res_node_num; ++u) { |
---|
972 | _next_out[u] = _first_out[u]; |
---|
973 | } |
---|
974 | |
---|
975 | // Perform partial augment and relabel operations |
---|
976 | while (true) { |
---|
977 | // Select an active node (FIFO selection) |
---|
978 | while (_active_nodes.size() > 0 && |
---|
979 | _excess[_active_nodes.front()] <= 0) { |
---|
980 | _active_nodes.pop_front(); |
---|
981 | } |
---|
982 | if (_active_nodes.size() == 0) break; |
---|
983 | int start = _active_nodes.front(); |
---|
984 | path_nodes.clear(); |
---|
985 | path_nodes.push_back(start); |
---|
986 | |
---|
987 | // Find an augmenting path from the start node |
---|
988 | int tip = start; |
---|
989 | while (_excess[tip] >= 0 && |
---|
990 | int(path_nodes.size()) <= max_length) { |
---|
991 | int u; |
---|
992 | LargeCost min_red_cost, rc; |
---|
993 | int last_out = _sum_supply < 0 ? |
---|
994 | _first_out[tip+1] : _first_out[tip+1] - 1; |
---|
995 | for (int a = _next_out[tip]; a != last_out; ++a) { |
---|
996 | if (_res_cap[a] > 0 && |
---|
997 | _cost[a] + _pi[_source[a]] - _pi[_target[a]] < 0) { |
---|
998 | u = _target[a]; |
---|
999 | pred_arc[u] = a; |
---|
1000 | _next_out[tip] = a; |
---|
1001 | tip = u; |
---|
1002 | path_nodes.push_back(tip); |
---|
1003 | goto next_step; |
---|
1004 | } |
---|
1005 | } |
---|
1006 | |
---|
1007 | // Relabel tip node |
---|
1008 | min_red_cost = std::numeric_limits<LargeCost>::max() / 2; |
---|
1009 | for (int a = _first_out[tip]; a != last_out; ++a) { |
---|
1010 | rc = _cost[a] + _pi[_source[a]] - _pi[_target[a]]; |
---|
1011 | if (_res_cap[a] > 0 && rc < min_red_cost) { |
---|
1012 | min_red_cost = rc; |
---|
1013 | } |
---|
1014 | } |
---|
1015 | _pi[tip] -= min_red_cost + _epsilon; |
---|
1016 | |
---|
1017 | // Reset the next arc of tip |
---|
1018 | _next_out[tip] = _first_out[tip]; |
---|
1019 | |
---|
1020 | // Step back |
---|
1021 | if (tip != start) { |
---|
1022 | path_nodes.pop_back(); |
---|
1023 | tip = path_nodes.back(); |
---|
1024 | } |
---|
1025 | |
---|
1026 | next_step: ; |
---|
1027 | } |
---|
1028 | |
---|
1029 | // Augment along the found path (as much flow as possible) |
---|
1030 | Value delta; |
---|
1031 | int u, v = path_nodes.front(), pa; |
---|
1032 | for (int i = 1; i < int(path_nodes.size()); ++i) { |
---|
1033 | u = v; |
---|
1034 | v = path_nodes[i]; |
---|
1035 | pa = pred_arc[v]; |
---|
1036 | delta = std::min(_res_cap[pa], _excess[u]); |
---|
1037 | _res_cap[pa] -= delta; |
---|
1038 | _res_cap[_reverse[pa]] += delta; |
---|
1039 | _excess[u] -= delta; |
---|
1040 | _excess[v] += delta; |
---|
1041 | if (_excess[v] > 0 && _excess[v] <= delta) |
---|
1042 | _active_nodes.push_back(v); |
---|
1043 | } |
---|
1044 | } |
---|
1045 | } |
---|
1046 | } |
---|
1047 | |
---|
1048 | /// Execute the algorithm performing push and relabel operations |
---|
1049 | void startPush() { |
---|
1050 | // Paramters for heuristics |
---|
1051 | const int BF_HEURISTIC_EPSILON_BOUND = 1000; |
---|
1052 | const int BF_HEURISTIC_BOUND_FACTOR = 3; |
---|
1053 | |
---|
1054 | // Perform cost scaling phases |
---|
1055 | BoolVector hyper(_res_node_num, false); |
---|
1056 | for ( ; _epsilon >= 1; _epsilon = _epsilon < _alpha && _epsilon > 1 ? |
---|
1057 | 1 : _epsilon / _alpha ) |
---|
1058 | { |
---|
1059 | // "Early Termination" heuristic: use Bellman-Ford algorithm |
---|
1060 | // to check if the current flow is optimal |
---|
1061 | if (_epsilon <= BF_HEURISTIC_EPSILON_BOUND) { |
---|
1062 | _arc_vec.clear(); |
---|
1063 | _cost_vec.clear(); |
---|
1064 | for (int j = 0; j != _res_arc_num; ++j) { |
---|
1065 | if (_res_cap[j] > 0) { |
---|
1066 | _arc_vec.push_back(IntPair(_source[j], _target[j])); |
---|
1067 | _cost_vec.push_back(_cost[j] + 1); |
---|
1068 | } |
---|
1069 | } |
---|
1070 | _sgr.build(_res_node_num, _arc_vec.begin(), _arc_vec.end()); |
---|
1071 | |
---|
1072 | BellmanFord<StaticDigraph, LargeCostArcMap> bf(_sgr, _cost_map); |
---|
1073 | bf.init(0); |
---|
1074 | bool done = false; |
---|
1075 | int K = int(BF_HEURISTIC_BOUND_FACTOR * sqrt(_res_node_num)); |
---|
1076 | for (int i = 0; i < K && !done; ++i) |
---|
1077 | done = bf.processNextWeakRound(); |
---|
1078 | if (done) break; |
---|
1079 | } |
---|
1080 | |
---|
1081 | // Saturate arcs not satisfying the optimality condition |
---|
1082 | for (int a = 0; a != _res_arc_num; ++a) { |
---|
1083 | if (_res_cap[a] > 0 && |
---|
1084 | _cost[a] + _pi[_source[a]] - _pi[_target[a]] < 0) { |
---|
1085 | Value delta = _res_cap[a]; |
---|
1086 | _excess[_source[a]] -= delta; |
---|
1087 | _excess[_target[a]] += delta; |
---|
1088 | _res_cap[a] = 0; |
---|
1089 | _res_cap[_reverse[a]] += delta; |
---|
1090 | } |
---|
1091 | } |
---|
1092 | |
---|
1093 | // Find active nodes (i.e. nodes with positive excess) |
---|
1094 | for (int u = 0; u != _res_node_num; ++u) { |
---|
1095 | if (_excess[u] > 0) _active_nodes.push_back(u); |
---|
1096 | } |
---|
1097 | |
---|
1098 | // Initialize the next arcs |
---|
1099 | for (int u = 0; u != _res_node_num; ++u) { |
---|
1100 | _next_out[u] = _first_out[u]; |
---|
1101 | } |
---|
1102 | |
---|
1103 | // Perform push and relabel operations |
---|
1104 | while (_active_nodes.size() > 0) { |
---|
1105 | LargeCost min_red_cost, rc; |
---|
1106 | Value delta; |
---|
1107 | int n, t, a, last_out = _res_arc_num; |
---|
1108 | |
---|
1109 | // Select an active node (FIFO selection) |
---|
1110 | next_node: |
---|
1111 | n = _active_nodes.front(); |
---|
1112 | last_out = _sum_supply < 0 ? |
---|
1113 | _first_out[n+1] : _first_out[n+1] - 1; |
---|
1114 | |
---|
1115 | // Perform push operations if there are admissible arcs |
---|
1116 | if (_excess[n] > 0) { |
---|
1117 | for (a = _next_out[n]; a != last_out; ++a) { |
---|
1118 | if (_res_cap[a] > 0 && |
---|
1119 | _cost[a] + _pi[_source[a]] - _pi[_target[a]] < 0) { |
---|
1120 | delta = std::min(_res_cap[a], _excess[n]); |
---|
1121 | t = _target[a]; |
---|
1122 | |
---|
1123 | // Push-look-ahead heuristic |
---|
1124 | Value ahead = -_excess[t]; |
---|
1125 | int last_out_t = _sum_supply < 0 ? |
---|
1126 | _first_out[t+1] : _first_out[t+1] - 1; |
---|
1127 | for (int ta = _next_out[t]; ta != last_out_t; ++ta) { |
---|
1128 | if (_res_cap[ta] > 0 && |
---|
1129 | _cost[ta] + _pi[_source[ta]] - _pi[_target[ta]] < 0) |
---|
1130 | ahead += _res_cap[ta]; |
---|
1131 | if (ahead >= delta) break; |
---|
1132 | } |
---|
1133 | if (ahead < 0) ahead = 0; |
---|
1134 | |
---|
1135 | // Push flow along the arc |
---|
1136 | if (ahead < delta) { |
---|
1137 | _res_cap[a] -= ahead; |
---|
1138 | _res_cap[_reverse[a]] += ahead; |
---|
1139 | _excess[n] -= ahead; |
---|
1140 | _excess[t] += ahead; |
---|
1141 | _active_nodes.push_front(t); |
---|
1142 | hyper[t] = true; |
---|
1143 | _next_out[n] = a; |
---|
1144 | goto next_node; |
---|
1145 | } else { |
---|
1146 | _res_cap[a] -= delta; |
---|
1147 | _res_cap[_reverse[a]] += delta; |
---|
1148 | _excess[n] -= delta; |
---|
1149 | _excess[t] += delta; |
---|
1150 | if (_excess[t] > 0 && _excess[t] <= delta) |
---|
1151 | _active_nodes.push_back(t); |
---|
1152 | } |
---|
1153 | |
---|
1154 | if (_excess[n] == 0) { |
---|
1155 | _next_out[n] = a; |
---|
1156 | goto remove_nodes; |
---|
1157 | } |
---|
1158 | } |
---|
1159 | } |
---|
1160 | _next_out[n] = a; |
---|
1161 | } |
---|
1162 | |
---|
1163 | // Relabel the node if it is still active (or hyper) |
---|
1164 | if (_excess[n] > 0 || hyper[n]) { |
---|
1165 | min_red_cost = std::numeric_limits<LargeCost>::max() / 2; |
---|
1166 | for (int a = _first_out[n]; a != last_out; ++a) { |
---|
1167 | rc = _cost[a] + _pi[_source[a]] - _pi[_target[a]]; |
---|
1168 | if (_res_cap[a] > 0 && rc < min_red_cost) { |
---|
1169 | min_red_cost = rc; |
---|
1170 | } |
---|
1171 | } |
---|
1172 | _pi[n] -= min_red_cost + _epsilon; |
---|
1173 | hyper[n] = false; |
---|
1174 | |
---|
1175 | // Reset the next arc |
---|
1176 | _next_out[n] = _first_out[n]; |
---|
1177 | } |
---|
1178 | |
---|
1179 | // Remove nodes that are not active nor hyper |
---|
1180 | remove_nodes: |
---|
1181 | while ( _active_nodes.size() > 0 && |
---|
1182 | _excess[_active_nodes.front()] <= 0 && |
---|
1183 | !hyper[_active_nodes.front()] ) { |
---|
1184 | _active_nodes.pop_front(); |
---|
1185 | } |
---|
1186 | } |
---|
1187 | } |
---|
1188 | } |
---|
1189 | |
---|
1190 | }; //class CostScaling |
---|
1191 | |
---|
1192 | ///@} |
---|
1193 | |
---|
1194 | } //namespace lemon |
---|
1195 | |
---|
1196 | #endif //LEMON_COST_SCALING_H |
---|