[956] | 1 | /* -*- mode: C++; indent-tabs-mode: nil; -*- |
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[874] | 2 | * |
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[956] | 3 | * This file is a part of LEMON, a generic C++ optimization library. |
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[874] | 4 | * |
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[956] | 5 | * Copyright (C) 2003-2010 |
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[874] | 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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[875] | 33 | #include <lemon/static_graph.h> |
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[874] | 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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[875] | 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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[878] | 43 | /// \tparam V The number type used for flow amounts, capacity bounds |
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[875] | 44 | /// and supply values. By default it is \c int. |
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[878] | 45 | /// \tparam C The number type used for costs and potentials. |
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[875] | 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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[874] | 86 | /// \addtogroup min_cost_flow_algs |
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| 87 | /// @{ |
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| 88 | |
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[875] | 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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[874] | 91 | /// |
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[875] | 92 | /// \ref CostScaling implements a cost scaling algorithm that performs |
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[879] | 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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[956] | 95 | /// \ref goldberg97efficient, \ref bunnagel98efficient. |
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[879] | 96 | /// It is a highly efficient primal-dual solution method, which |
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[875] | 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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[874] | 99 | /// |
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[1023] | 100 | /// In general, \ref NetworkSimplex and \ref CostScaling are the fastest |
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| 101 | /// implementations available in LEMON for this problem. |
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| 102 | /// |
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[875] | 103 | /// Most of the parameters of the problem (except for the digraph) |
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| 104 | /// can be given using separate functions, and the algorithm can be |
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| 105 | /// executed using the \ref run() function. If some parameters are not |
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| 106 | /// specified, then default values will be used. |
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[874] | 107 | /// |
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[875] | 108 | /// \tparam GR The digraph type the algorithm runs on. |
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[878] | 109 | /// \tparam V The number type used for flow amounts, capacity bounds |
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[891] | 110 | /// and supply values in the algorithm. By default, it is \c int. |
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[878] | 111 | /// \tparam C The number type used for costs and potentials in the |
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[891] | 112 | /// algorithm. By default, it is the same as \c V. |
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| 113 | /// \tparam TR The traits class that defines various types used by the |
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| 114 | /// algorithm. By default, it is \ref CostScalingDefaultTraits |
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| 115 | /// "CostScalingDefaultTraits<GR, V, C>". |
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| 116 | /// In most cases, this parameter should not be set directly, |
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| 117 | /// consider to use the named template parameters instead. |
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[874] | 118 | /// |
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[1025] | 119 | /// \warning Both \c V and \c C must be signed number types. |
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| 120 | /// \warning All input data (capacities, supply values, and costs) must |
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[875] | 121 | /// be integer. |
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[1023] | 122 | /// \warning This algorithm does not support negative costs for |
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| 123 | /// arcs having infinite upper bound. |
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[876] | 124 | /// |
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| 125 | /// \note %CostScaling provides three different internal methods, |
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| 126 | /// from which the most efficient one is used by default. |
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| 127 | /// For more information, see \ref Method. |
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[875] | 128 | #ifdef DOXYGEN |
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| 129 | template <typename GR, typename V, typename C, typename TR> |
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| 130 | #else |
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| 131 | template < typename GR, typename V = int, typename C = V, |
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| 132 | typename TR = CostScalingDefaultTraits<GR, V, C> > |
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| 133 | #endif |
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[874] | 134 | class CostScaling |
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| 135 | { |
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[875] | 136 | public: |
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[874] | 137 | |
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[875] | 138 | /// The type of the digraph |
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| 139 | typedef typename TR::Digraph Digraph; |
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| 140 | /// The type of the flow amounts, capacity bounds and supply values |
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| 141 | typedef typename TR::Value Value; |
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| 142 | /// The type of the arc costs |
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| 143 | typedef typename TR::Cost Cost; |
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[874] | 144 | |
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[875] | 145 | /// \brief The large cost type |
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| 146 | /// |
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| 147 | /// The large cost type used for internal computations. |
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[891] | 148 | /// By default, it is \c long \c long if the \c Cost type is integer, |
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[875] | 149 | /// otherwise it is \c double. |
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| 150 | typedef typename TR::LargeCost LargeCost; |
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[874] | 151 | |
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[875] | 152 | /// The \ref CostScalingDefaultTraits "traits class" of the algorithm |
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| 153 | typedef TR Traits; |
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[874] | 154 | |
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| 155 | public: |
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| 156 | |
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[875] | 157 | /// \brief Problem type constants for the \c run() function. |
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| 158 | /// |
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| 159 | /// Enum type containing the problem type constants that can be |
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| 160 | /// returned by the \ref run() function of the algorithm. |
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| 161 | enum ProblemType { |
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| 162 | /// The problem has no feasible solution (flow). |
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| 163 | INFEASIBLE, |
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| 164 | /// The problem has optimal solution (i.e. it is feasible and |
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| 165 | /// bounded), and the algorithm has found optimal flow and node |
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| 166 | /// potentials (primal and dual solutions). |
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| 167 | OPTIMAL, |
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| 168 | /// The digraph contains an arc of negative cost and infinite |
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| 169 | /// upper bound. It means that the objective function is unbounded |
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[878] | 170 | /// on that arc, however, note that it could actually be bounded |
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[875] | 171 | /// over the feasible flows, but this algroithm cannot handle |
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| 172 | /// these cases. |
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| 173 | UNBOUNDED |
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| 174 | }; |
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[874] | 175 | |
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[876] | 176 | /// \brief Constants for selecting the internal method. |
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| 177 | /// |
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| 178 | /// Enum type containing constants for selecting the internal method |
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| 179 | /// for the \ref run() function. |
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| 180 | /// |
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| 181 | /// \ref CostScaling provides three internal methods that differ mainly |
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| 182 | /// in their base operations, which are used in conjunction with the |
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| 183 | /// relabel operation. |
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| 184 | /// By default, the so called \ref PARTIAL_AUGMENT |
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[1023] | 185 | /// "Partial Augment-Relabel" method is used, which turned out to be |
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[876] | 186 | /// the most efficient and the most robust on various test inputs. |
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| 187 | /// However, the other methods can be selected using the \ref run() |
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| 188 | /// function with the proper parameter. |
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| 189 | enum Method { |
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| 190 | /// Local push operations are used, i.e. flow is moved only on one |
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| 191 | /// admissible arc at once. |
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| 192 | PUSH, |
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| 193 | /// Augment operations are used, i.e. flow is moved on admissible |
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| 194 | /// paths from a node with excess to a node with deficit. |
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| 195 | AUGMENT, |
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[956] | 196 | /// Partial augment operations are used, i.e. flow is moved on |
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[876] | 197 | /// admissible paths started from a node with excess, but the |
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| 198 | /// lengths of these paths are limited. This method can be viewed |
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| 199 | /// as a combined version of the previous two operations. |
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| 200 | PARTIAL_AUGMENT |
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| 201 | }; |
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| 202 | |
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[874] | 203 | private: |
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| 204 | |
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[875] | 205 | TEMPLATE_DIGRAPH_TYPEDEFS(GR); |
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[874] | 206 | |
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[875] | 207 | typedef std::vector<int> IntVector; |
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| 208 | typedef std::vector<Value> ValueVector; |
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| 209 | typedef std::vector<Cost> CostVector; |
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| 210 | typedef std::vector<LargeCost> LargeCostVector; |
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[910] | 211 | typedef std::vector<char> BoolVector; |
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| 212 | // Note: vector<char> is used instead of vector<bool> for efficiency reasons |
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[874] | 213 | |
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[875] | 214 | private: |
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[956] | 215 | |
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[875] | 216 | template <typename KT, typename VT> |
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[886] | 217 | class StaticVectorMap { |
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[874] | 218 | public: |
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[875] | 219 | typedef KT Key; |
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| 220 | typedef VT Value; |
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[956] | 221 | |
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[886] | 222 | StaticVectorMap(std::vector<Value>& v) : _v(v) {} |
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[956] | 223 | |
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[875] | 224 | const Value& operator[](const Key& key) const { |
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| 225 | return _v[StaticDigraph::id(key)]; |
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[874] | 226 | } |
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| 227 | |
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[875] | 228 | Value& operator[](const Key& key) { |
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| 229 | return _v[StaticDigraph::id(key)]; |
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| 230 | } |
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[956] | 231 | |
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[875] | 232 | void set(const Key& key, const Value& val) { |
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| 233 | _v[StaticDigraph::id(key)] = val; |
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[874] | 234 | } |
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| 235 | |
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[875] | 236 | private: |
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| 237 | std::vector<Value>& _v; |
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| 238 | }; |
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| 239 | |
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[886] | 240 | typedef StaticVectorMap<StaticDigraph::Arc, LargeCost> LargeCostArcMap; |
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[874] | 241 | |
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| 242 | private: |
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| 243 | |
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[875] | 244 | // Data related to the underlying digraph |
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| 245 | const GR &_graph; |
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| 246 | int _node_num; |
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| 247 | int _arc_num; |
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| 248 | int _res_node_num; |
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| 249 | int _res_arc_num; |
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| 250 | int _root; |
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[874] | 251 | |
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[875] | 252 | // Parameters of the problem |
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| 253 | bool _have_lower; |
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| 254 | Value _sum_supply; |
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[910] | 255 | int _sup_node_num; |
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[874] | 256 | |
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[875] | 257 | // Data structures for storing the digraph |
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| 258 | IntNodeMap _node_id; |
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| 259 | IntArcMap _arc_idf; |
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| 260 | IntArcMap _arc_idb; |
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| 261 | IntVector _first_out; |
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| 262 | BoolVector _forward; |
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| 263 | IntVector _source; |
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| 264 | IntVector _target; |
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| 265 | IntVector _reverse; |
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| 266 | |
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| 267 | // Node and arc data |
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| 268 | ValueVector _lower; |
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| 269 | ValueVector _upper; |
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| 270 | CostVector _scost; |
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| 271 | ValueVector _supply; |
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| 272 | |
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| 273 | ValueVector _res_cap; |
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| 274 | LargeCostVector _cost; |
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| 275 | LargeCostVector _pi; |
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| 276 | ValueVector _excess; |
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| 277 | IntVector _next_out; |
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| 278 | std::deque<int> _active_nodes; |
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| 279 | |
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| 280 | // Data for scaling |
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| 281 | LargeCost _epsilon; |
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[874] | 282 | int _alpha; |
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| 283 | |
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[910] | 284 | IntVector _buckets; |
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| 285 | IntVector _bucket_next; |
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| 286 | IntVector _bucket_prev; |
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| 287 | IntVector _rank; |
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| 288 | int _max_rank; |
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[956] | 289 | |
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[875] | 290 | public: |
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[956] | 291 | |
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[875] | 292 | /// \brief Constant for infinite upper bounds (capacities). |
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| 293 | /// |
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| 294 | /// Constant for infinite upper bounds (capacities). |
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| 295 | /// It is \c std::numeric_limits<Value>::infinity() if available, |
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| 296 | /// \c std::numeric_limits<Value>::max() otherwise. |
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| 297 | const Value INF; |
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| 298 | |
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[874] | 299 | public: |
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| 300 | |
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[875] | 301 | /// \name Named Template Parameters |
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| 302 | /// @{ |
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| 303 | |
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| 304 | template <typename T> |
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| 305 | struct SetLargeCostTraits : public Traits { |
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| 306 | typedef T LargeCost; |
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| 307 | }; |
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| 308 | |
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| 309 | /// \brief \ref named-templ-param "Named parameter" for setting |
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| 310 | /// \c LargeCost type. |
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[874] | 311 | /// |
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[875] | 312 | /// \ref named-templ-param "Named parameter" for setting \c LargeCost |
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| 313 | /// type, which is used for internal computations in the algorithm. |
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| 314 | /// \c Cost must be convertible to \c LargeCost. |
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| 315 | template <typename T> |
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| 316 | struct SetLargeCost |
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| 317 | : public CostScaling<GR, V, C, SetLargeCostTraits<T> > { |
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| 318 | typedef CostScaling<GR, V, C, SetLargeCostTraits<T> > Create; |
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| 319 | }; |
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| 320 | |
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| 321 | /// @} |
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| 322 | |
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[941] | 323 | protected: |
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| 324 | |
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| 325 | CostScaling() {} |
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| 326 | |
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[875] | 327 | public: |
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| 328 | |
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| 329 | /// \brief Constructor. |
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[874] | 330 | /// |
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[875] | 331 | /// The constructor of the class. |
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| 332 | /// |
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| 333 | /// \param graph The digraph the algorithm runs on. |
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| 334 | CostScaling(const GR& graph) : |
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| 335 | _graph(graph), _node_id(graph), _arc_idf(graph), _arc_idb(graph), |
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| 336 | INF(std::numeric_limits<Value>::has_infinity ? |
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| 337 | std::numeric_limits<Value>::infinity() : |
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| 338 | std::numeric_limits<Value>::max()) |
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[874] | 339 | { |
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[878] | 340 | // Check the number types |
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[875] | 341 | LEMON_ASSERT(std::numeric_limits<Value>::is_signed, |
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| 342 | "The flow type of CostScaling must be signed"); |
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| 343 | LEMON_ASSERT(std::numeric_limits<Cost>::is_signed, |
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| 344 | "The cost type of CostScaling must be signed"); |
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[956] | 345 | |
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[898] | 346 | // Reset data structures |
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[875] | 347 | reset(); |
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[874] | 348 | } |
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| 349 | |
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[875] | 350 | /// \name Parameters |
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| 351 | /// The parameters of the algorithm can be specified using these |
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| 352 | /// functions. |
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| 353 | |
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| 354 | /// @{ |
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| 355 | |
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| 356 | /// \brief Set the lower bounds on the arcs. |
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[874] | 357 | /// |
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[875] | 358 | /// This function sets the lower bounds on the arcs. |
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| 359 | /// If it is not used before calling \ref run(), the lower bounds |
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| 360 | /// will be set to zero on all arcs. |
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[874] | 361 | /// |
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[875] | 362 | /// \param map An arc map storing the lower bounds. |
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| 363 | /// Its \c Value type must be convertible to the \c Value type |
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| 364 | /// of the algorithm. |
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| 365 | /// |
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| 366 | /// \return <tt>(*this)</tt> |
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| 367 | template <typename LowerMap> |
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| 368 | CostScaling& lowerMap(const LowerMap& map) { |
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| 369 | _have_lower = true; |
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| 370 | for (ArcIt a(_graph); a != INVALID; ++a) { |
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| 371 | _lower[_arc_idf[a]] = map[a]; |
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| 372 | _lower[_arc_idb[a]] = map[a]; |
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[874] | 373 | } |
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| 374 | return *this; |
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| 375 | } |
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| 376 | |
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[875] | 377 | /// \brief Set the upper bounds (capacities) on the arcs. |
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[874] | 378 | /// |
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[875] | 379 | /// This function sets the upper bounds (capacities) on the arcs. |
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| 380 | /// If it is not used before calling \ref run(), the upper bounds |
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| 381 | /// will be set to \ref INF on all arcs (i.e. the flow value will be |
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[878] | 382 | /// unbounded from above). |
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[874] | 383 | /// |
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[875] | 384 | /// \param map An arc map storing the upper bounds. |
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| 385 | /// Its \c Value type must be convertible to the \c Value type |
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| 386 | /// of the algorithm. |
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| 387 | /// |
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| 388 | /// \return <tt>(*this)</tt> |
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| 389 | template<typename UpperMap> |
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| 390 | CostScaling& upperMap(const UpperMap& map) { |
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| 391 | for (ArcIt a(_graph); a != INVALID; ++a) { |
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| 392 | _upper[_arc_idf[a]] = map[a]; |
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[874] | 393 | } |
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| 394 | return *this; |
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| 395 | } |
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| 396 | |
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[875] | 397 | /// \brief Set the costs of the arcs. |
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| 398 | /// |
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| 399 | /// This function sets the costs of the arcs. |
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| 400 | /// If it is not used before calling \ref run(), the costs |
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| 401 | /// will be set to \c 1 on all arcs. |
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| 402 | /// |
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| 403 | /// \param map An arc map storing the costs. |
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| 404 | /// Its \c Value type must be convertible to the \c Cost type |
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| 405 | /// of the algorithm. |
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| 406 | /// |
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| 407 | /// \return <tt>(*this)</tt> |
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| 408 | template<typename CostMap> |
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| 409 | CostScaling& costMap(const CostMap& map) { |
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| 410 | for (ArcIt a(_graph); a != INVALID; ++a) { |
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| 411 | _scost[_arc_idf[a]] = map[a]; |
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| 412 | _scost[_arc_idb[a]] = -map[a]; |
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| 413 | } |
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| 414 | return *this; |
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| 415 | } |
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| 416 | |
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| 417 | /// \brief Set the supply values of the nodes. |
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| 418 | /// |
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| 419 | /// This function sets the supply values of the nodes. |
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| 420 | /// If neither this function nor \ref stSupply() is used before |
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| 421 | /// calling \ref run(), the supply of each node will be set to zero. |
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| 422 | /// |
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| 423 | /// \param map A node map storing the supply values. |
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| 424 | /// Its \c Value type must be convertible to the \c Value type |
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| 425 | /// of the algorithm. |
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| 426 | /// |
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| 427 | /// \return <tt>(*this)</tt> |
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| 428 | template<typename SupplyMap> |
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| 429 | CostScaling& supplyMap(const SupplyMap& map) { |
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| 430 | for (NodeIt n(_graph); n != INVALID; ++n) { |
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| 431 | _supply[_node_id[n]] = map[n]; |
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| 432 | } |
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| 433 | return *this; |
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| 434 | } |
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| 435 | |
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| 436 | /// \brief Set single source and target nodes and a supply value. |
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| 437 | /// |
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| 438 | /// This function sets a single source node and a single target node |
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| 439 | /// and the required flow value. |
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| 440 | /// If neither this function nor \ref supplyMap() is used before |
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| 441 | /// calling \ref run(), the supply of each node will be set to zero. |
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| 442 | /// |
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| 443 | /// Using this function has the same effect as using \ref supplyMap() |
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[1023] | 444 | /// with a map in which \c k is assigned to \c s, \c -k is |
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[875] | 445 | /// assigned to \c t and all other nodes have zero supply value. |
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| 446 | /// |
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| 447 | /// \param s The source node. |
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| 448 | /// \param t The target node. |
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| 449 | /// \param k The required amount of flow from node \c s to node \c t |
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| 450 | /// (i.e. the supply of \c s and the demand of \c t). |
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| 451 | /// |
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| 452 | /// \return <tt>(*this)</tt> |
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| 453 | CostScaling& stSupply(const Node& s, const Node& t, Value k) { |
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| 454 | for (int i = 0; i != _res_node_num; ++i) { |
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| 455 | _supply[i] = 0; |
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| 456 | } |
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| 457 | _supply[_node_id[s]] = k; |
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| 458 | _supply[_node_id[t]] = -k; |
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| 459 | return *this; |
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| 460 | } |
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[956] | 461 | |
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[875] | 462 | /// @} |
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| 463 | |
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[874] | 464 | /// \name Execution control |
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[875] | 465 | /// The algorithm can be executed using \ref run(). |
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[874] | 466 | |
---|
| 467 | /// @{ |
---|
| 468 | |
---|
| 469 | /// \brief Run the algorithm. |
---|
| 470 | /// |
---|
[875] | 471 | /// This function runs the algorithm. |
---|
| 472 | /// The paramters can be specified using functions \ref lowerMap(), |
---|
| 473 | /// \ref upperMap(), \ref costMap(), \ref supplyMap(), \ref stSupply(). |
---|
| 474 | /// For example, |
---|
| 475 | /// \code |
---|
| 476 | /// CostScaling<ListDigraph> cs(graph); |
---|
| 477 | /// cs.lowerMap(lower).upperMap(upper).costMap(cost) |
---|
| 478 | /// .supplyMap(sup).run(); |
---|
| 479 | /// \endcode |
---|
| 480 | /// |
---|
[898] | 481 | /// This function can be called more than once. All the given parameters |
---|
| 482 | /// are kept for the next call, unless \ref resetParams() or \ref reset() |
---|
| 483 | /// is used, thus only the modified parameters have to be set again. |
---|
| 484 | /// If the underlying digraph was also modified after the construction |
---|
| 485 | /// of the class (or the last \ref reset() call), then the \ref reset() |
---|
| 486 | /// function must be called. |
---|
[874] | 487 | /// |
---|
[876] | 488 | /// \param method The internal method that will be used in the |
---|
| 489 | /// algorithm. For more information, see \ref Method. |
---|
[1049] | 490 | /// \param factor The cost scaling factor. It must be at least two. |
---|
[874] | 491 | /// |
---|
[875] | 492 | /// \return \c INFEASIBLE if no feasible flow exists, |
---|
| 493 | /// \n \c OPTIMAL if the problem has optimal solution |
---|
| 494 | /// (i.e. it is feasible and bounded), and the algorithm has found |
---|
| 495 | /// optimal flow and node potentials (primal and dual solutions), |
---|
| 496 | /// \n \c UNBOUNDED if the digraph contains an arc of negative cost |
---|
| 497 | /// and infinite upper bound. It means that the objective function |
---|
[878] | 498 | /// is unbounded on that arc, however, note that it could actually be |
---|
[875] | 499 | /// bounded over the feasible flows, but this algroithm cannot handle |
---|
| 500 | /// these cases. |
---|
| 501 | /// |
---|
[876] | 502 | /// \see ProblemType, Method |
---|
[898] | 503 | /// \see resetParams(), reset() |
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[1049] | 504 | ProblemType run(Method method = PARTIAL_AUGMENT, int factor = 16) { |
---|
| 505 | LEMON_ASSERT(factor >= 2, "The scaling factor must be at least 2"); |
---|
[876] | 506 | _alpha = factor; |
---|
[875] | 507 | ProblemType pt = init(); |
---|
| 508 | if (pt != OPTIMAL) return pt; |
---|
[876] | 509 | start(method); |
---|
[875] | 510 | return OPTIMAL; |
---|
| 511 | } |
---|
| 512 | |
---|
| 513 | /// \brief Reset all the parameters that have been given before. |
---|
| 514 | /// |
---|
| 515 | /// This function resets all the paramaters that have been given |
---|
| 516 | /// before using functions \ref lowerMap(), \ref upperMap(), |
---|
| 517 | /// \ref costMap(), \ref supplyMap(), \ref stSupply(). |
---|
| 518 | /// |
---|
[898] | 519 | /// It is useful for multiple \ref run() calls. Basically, all the given |
---|
| 520 | /// parameters are kept for the next \ref run() call, unless |
---|
| 521 | /// \ref resetParams() or \ref reset() is used. |
---|
| 522 | /// If the underlying digraph was also modified after the construction |
---|
| 523 | /// of the class or the last \ref reset() call, then the \ref reset() |
---|
| 524 | /// function must be used, otherwise \ref resetParams() is sufficient. |
---|
[875] | 525 | /// |
---|
| 526 | /// For example, |
---|
| 527 | /// \code |
---|
| 528 | /// CostScaling<ListDigraph> cs(graph); |
---|
| 529 | /// |
---|
| 530 | /// // First run |
---|
| 531 | /// cs.lowerMap(lower).upperMap(upper).costMap(cost) |
---|
| 532 | /// .supplyMap(sup).run(); |
---|
| 533 | /// |
---|
[898] | 534 | /// // Run again with modified cost map (resetParams() is not called, |
---|
[875] | 535 | /// // so only the cost map have to be set again) |
---|
| 536 | /// cost[e] += 100; |
---|
| 537 | /// cs.costMap(cost).run(); |
---|
| 538 | /// |
---|
[898] | 539 | /// // Run again from scratch using resetParams() |
---|
[875] | 540 | /// // (the lower bounds will be set to zero on all arcs) |
---|
[898] | 541 | /// cs.resetParams(); |
---|
[875] | 542 | /// cs.upperMap(capacity).costMap(cost) |
---|
| 543 | /// .supplyMap(sup).run(); |
---|
| 544 | /// \endcode |
---|
| 545 | /// |
---|
| 546 | /// \return <tt>(*this)</tt> |
---|
[898] | 547 | /// |
---|
| 548 | /// \see reset(), run() |
---|
| 549 | CostScaling& resetParams() { |
---|
[875] | 550 | for (int i = 0; i != _res_node_num; ++i) { |
---|
| 551 | _supply[i] = 0; |
---|
[874] | 552 | } |
---|
[875] | 553 | int limit = _first_out[_root]; |
---|
| 554 | for (int j = 0; j != limit; ++j) { |
---|
| 555 | _lower[j] = 0; |
---|
| 556 | _upper[j] = INF; |
---|
| 557 | _scost[j] = _forward[j] ? 1 : -1; |
---|
| 558 | } |
---|
| 559 | for (int j = limit; j != _res_arc_num; ++j) { |
---|
| 560 | _lower[j] = 0; |
---|
| 561 | _upper[j] = INF; |
---|
| 562 | _scost[j] = 0; |
---|
| 563 | _scost[_reverse[j]] = 0; |
---|
[956] | 564 | } |
---|
[875] | 565 | _have_lower = false; |
---|
| 566 | return *this; |
---|
[874] | 567 | } |
---|
| 568 | |
---|
[1045] | 569 | /// \brief Reset the internal data structures and all the parameters |
---|
| 570 | /// that have been given before. |
---|
[898] | 571 | /// |
---|
[1045] | 572 | /// This function resets the internal data structures and all the |
---|
| 573 | /// paramaters that have been given before using functions \ref lowerMap(), |
---|
| 574 | /// \ref upperMap(), \ref costMap(), \ref supplyMap(), \ref stSupply(). |
---|
[898] | 575 | /// |
---|
[1045] | 576 | /// It is useful for multiple \ref run() calls. By default, all the given |
---|
| 577 | /// parameters are kept for the next \ref run() call, unless |
---|
| 578 | /// \ref resetParams() or \ref reset() is used. |
---|
| 579 | /// If the underlying digraph was also modified after the construction |
---|
| 580 | /// of the class or the last \ref reset() call, then the \ref reset() |
---|
| 581 | /// function must be used, otherwise \ref resetParams() is sufficient. |
---|
| 582 | /// |
---|
| 583 | /// See \ref resetParams() for examples. |
---|
| 584 | /// |
---|
[898] | 585 | /// \return <tt>(*this)</tt> |
---|
[1045] | 586 | /// |
---|
| 587 | /// \see resetParams(), run() |
---|
[898] | 588 | CostScaling& reset() { |
---|
| 589 | // Resize vectors |
---|
| 590 | _node_num = countNodes(_graph); |
---|
| 591 | _arc_num = countArcs(_graph); |
---|
| 592 | _res_node_num = _node_num + 1; |
---|
| 593 | _res_arc_num = 2 * (_arc_num + _node_num); |
---|
| 594 | _root = _node_num; |
---|
| 595 | |
---|
| 596 | _first_out.resize(_res_node_num + 1); |
---|
| 597 | _forward.resize(_res_arc_num); |
---|
| 598 | _source.resize(_res_arc_num); |
---|
| 599 | _target.resize(_res_arc_num); |
---|
| 600 | _reverse.resize(_res_arc_num); |
---|
| 601 | |
---|
| 602 | _lower.resize(_res_arc_num); |
---|
| 603 | _upper.resize(_res_arc_num); |
---|
| 604 | _scost.resize(_res_arc_num); |
---|
| 605 | _supply.resize(_res_node_num); |
---|
[956] | 606 | |
---|
[898] | 607 | _res_cap.resize(_res_arc_num); |
---|
| 608 | _cost.resize(_res_arc_num); |
---|
| 609 | _pi.resize(_res_node_num); |
---|
| 610 | _excess.resize(_res_node_num); |
---|
| 611 | _next_out.resize(_res_node_num); |
---|
| 612 | |
---|
| 613 | // Copy the graph |
---|
| 614 | int i = 0, j = 0, k = 2 * _arc_num + _node_num; |
---|
| 615 | for (NodeIt n(_graph); n != INVALID; ++n, ++i) { |
---|
| 616 | _node_id[n] = i; |
---|
| 617 | } |
---|
| 618 | i = 0; |
---|
| 619 | for (NodeIt n(_graph); n != INVALID; ++n, ++i) { |
---|
| 620 | _first_out[i] = j; |
---|
| 621 | for (OutArcIt a(_graph, n); a != INVALID; ++a, ++j) { |
---|
| 622 | _arc_idf[a] = j; |
---|
| 623 | _forward[j] = true; |
---|
| 624 | _source[j] = i; |
---|
| 625 | _target[j] = _node_id[_graph.runningNode(a)]; |
---|
| 626 | } |
---|
| 627 | for (InArcIt a(_graph, n); a != INVALID; ++a, ++j) { |
---|
| 628 | _arc_idb[a] = j; |
---|
| 629 | _forward[j] = false; |
---|
| 630 | _source[j] = i; |
---|
| 631 | _target[j] = _node_id[_graph.runningNode(a)]; |
---|
| 632 | } |
---|
| 633 | _forward[j] = false; |
---|
| 634 | _source[j] = i; |
---|
| 635 | _target[j] = _root; |
---|
| 636 | _reverse[j] = k; |
---|
| 637 | _forward[k] = true; |
---|
| 638 | _source[k] = _root; |
---|
| 639 | _target[k] = i; |
---|
| 640 | _reverse[k] = j; |
---|
| 641 | ++j; ++k; |
---|
| 642 | } |
---|
| 643 | _first_out[i] = j; |
---|
| 644 | _first_out[_res_node_num] = k; |
---|
| 645 | for (ArcIt a(_graph); a != INVALID; ++a) { |
---|
| 646 | int fi = _arc_idf[a]; |
---|
| 647 | int bi = _arc_idb[a]; |
---|
| 648 | _reverse[fi] = bi; |
---|
| 649 | _reverse[bi] = fi; |
---|
| 650 | } |
---|
[956] | 651 | |
---|
[898] | 652 | // Reset parameters |
---|
| 653 | resetParams(); |
---|
| 654 | return *this; |
---|
| 655 | } |
---|
| 656 | |
---|
[874] | 657 | /// @} |
---|
| 658 | |
---|
| 659 | /// \name Query Functions |
---|
[875] | 660 | /// The results of the algorithm can be obtained using these |
---|
[874] | 661 | /// functions.\n |
---|
[875] | 662 | /// The \ref run() function must be called before using them. |
---|
[874] | 663 | |
---|
| 664 | /// @{ |
---|
| 665 | |
---|
[875] | 666 | /// \brief Return the total cost of the found flow. |
---|
[874] | 667 | /// |
---|
[875] | 668 | /// This function returns the total cost of the found flow. |
---|
| 669 | /// Its complexity is O(e). |
---|
| 670 | /// |
---|
| 671 | /// \note The return type of the function can be specified as a |
---|
| 672 | /// template parameter. For example, |
---|
| 673 | /// \code |
---|
| 674 | /// cs.totalCost<double>(); |
---|
| 675 | /// \endcode |
---|
| 676 | /// It is useful if the total cost cannot be stored in the \c Cost |
---|
| 677 | /// type of the algorithm, which is the default return type of the |
---|
| 678 | /// function. |
---|
[874] | 679 | /// |
---|
| 680 | /// \pre \ref run() must be called before using this function. |
---|
[875] | 681 | template <typename Number> |
---|
| 682 | Number totalCost() const { |
---|
| 683 | Number c = 0; |
---|
| 684 | for (ArcIt a(_graph); a != INVALID; ++a) { |
---|
| 685 | int i = _arc_idb[a]; |
---|
| 686 | c += static_cast<Number>(_res_cap[i]) * |
---|
| 687 | (-static_cast<Number>(_scost[i])); |
---|
| 688 | } |
---|
| 689 | return c; |
---|
[874] | 690 | } |
---|
| 691 | |
---|
[875] | 692 | #ifndef DOXYGEN |
---|
| 693 | Cost totalCost() const { |
---|
| 694 | return totalCost<Cost>(); |
---|
[874] | 695 | } |
---|
[875] | 696 | #endif |
---|
[874] | 697 | |
---|
| 698 | /// \brief Return the flow on the given arc. |
---|
| 699 | /// |
---|
[875] | 700 | /// This function returns the flow on the given arc. |
---|
[874] | 701 | /// |
---|
| 702 | /// \pre \ref run() must be called before using this function. |
---|
[875] | 703 | Value flow(const Arc& a) const { |
---|
| 704 | return _res_cap[_arc_idb[a]]; |
---|
[874] | 705 | } |
---|
| 706 | |
---|
[875] | 707 | /// \brief Return the flow map (the primal solution). |
---|
[874] | 708 | /// |
---|
[875] | 709 | /// This function copies the flow value on each arc into the given |
---|
| 710 | /// map. The \c Value type of the algorithm must be convertible to |
---|
| 711 | /// the \c Value type of the map. |
---|
[874] | 712 | /// |
---|
| 713 | /// \pre \ref run() must be called before using this function. |
---|
[875] | 714 | template <typename FlowMap> |
---|
| 715 | void flowMap(FlowMap &map) const { |
---|
| 716 | for (ArcIt a(_graph); a != INVALID; ++a) { |
---|
| 717 | map.set(a, _res_cap[_arc_idb[a]]); |
---|
| 718 | } |
---|
[874] | 719 | } |
---|
| 720 | |
---|
[875] | 721 | /// \brief Return the potential (dual value) of the given node. |
---|
[874] | 722 | /// |
---|
[875] | 723 | /// This function returns the potential (dual value) of the |
---|
| 724 | /// given node. |
---|
[874] | 725 | /// |
---|
| 726 | /// \pre \ref run() must be called before using this function. |
---|
[875] | 727 | Cost potential(const Node& n) const { |
---|
| 728 | return static_cast<Cost>(_pi[_node_id[n]]); |
---|
| 729 | } |
---|
| 730 | |
---|
| 731 | /// \brief Return the potential map (the dual solution). |
---|
| 732 | /// |
---|
| 733 | /// This function copies the potential (dual value) of each node |
---|
| 734 | /// into the given map. |
---|
| 735 | /// The \c Cost type of the algorithm must be convertible to the |
---|
| 736 | /// \c Value type of the map. |
---|
| 737 | /// |
---|
| 738 | /// \pre \ref run() must be called before using this function. |
---|
| 739 | template <typename PotentialMap> |
---|
| 740 | void potentialMap(PotentialMap &map) const { |
---|
| 741 | for (NodeIt n(_graph); n != INVALID; ++n) { |
---|
| 742 | map.set(n, static_cast<Cost>(_pi[_node_id[n]])); |
---|
| 743 | } |
---|
[874] | 744 | } |
---|
| 745 | |
---|
| 746 | /// @} |
---|
| 747 | |
---|
| 748 | private: |
---|
| 749 | |
---|
[875] | 750 | // Initialize the algorithm |
---|
| 751 | ProblemType init() { |
---|
[887] | 752 | if (_res_node_num <= 1) return INFEASIBLE; |
---|
[875] | 753 | |
---|
| 754 | // Check the sum of supply values |
---|
| 755 | _sum_supply = 0; |
---|
| 756 | for (int i = 0; i != _root; ++i) { |
---|
| 757 | _sum_supply += _supply[i]; |
---|
[874] | 758 | } |
---|
[875] | 759 | if (_sum_supply > 0) return INFEASIBLE; |
---|
[956] | 760 | |
---|
[875] | 761 | |
---|
| 762 | // Initialize vectors |
---|
| 763 | for (int i = 0; i != _res_node_num; ++i) { |
---|
| 764 | _pi[i] = 0; |
---|
| 765 | _excess[i] = _supply[i]; |
---|
| 766 | } |
---|
[956] | 767 | |
---|
[875] | 768 | // Remove infinite upper bounds and check negative arcs |
---|
| 769 | const Value MAX = std::numeric_limits<Value>::max(); |
---|
| 770 | int last_out; |
---|
| 771 | if (_have_lower) { |
---|
| 772 | for (int i = 0; i != _root; ++i) { |
---|
| 773 | last_out = _first_out[i+1]; |
---|
| 774 | for (int j = _first_out[i]; j != last_out; ++j) { |
---|
| 775 | if (_forward[j]) { |
---|
| 776 | Value c = _scost[j] < 0 ? _upper[j] : _lower[j]; |
---|
| 777 | if (c >= MAX) return UNBOUNDED; |
---|
| 778 | _excess[i] -= c; |
---|
| 779 | _excess[_target[j]] += c; |
---|
| 780 | } |
---|
| 781 | } |
---|
| 782 | } |
---|
| 783 | } else { |
---|
| 784 | for (int i = 0; i != _root; ++i) { |
---|
| 785 | last_out = _first_out[i+1]; |
---|
| 786 | for (int j = _first_out[i]; j != last_out; ++j) { |
---|
| 787 | if (_forward[j] && _scost[j] < 0) { |
---|
| 788 | Value c = _upper[j]; |
---|
| 789 | if (c >= MAX) return UNBOUNDED; |
---|
| 790 | _excess[i] -= c; |
---|
| 791 | _excess[_target[j]] += c; |
---|
| 792 | } |
---|
| 793 | } |
---|
| 794 | } |
---|
| 795 | } |
---|
| 796 | Value ex, max_cap = 0; |
---|
| 797 | for (int i = 0; i != _res_node_num; ++i) { |
---|
| 798 | ex = _excess[i]; |
---|
| 799 | _excess[i] = 0; |
---|
| 800 | if (ex < 0) max_cap -= ex; |
---|
| 801 | } |
---|
| 802 | for (int j = 0; j != _res_arc_num; ++j) { |
---|
| 803 | if (_upper[j] >= MAX) _upper[j] = max_cap; |
---|
[874] | 804 | } |
---|
| 805 | |
---|
[875] | 806 | // Initialize the large cost vector and the epsilon parameter |
---|
| 807 | _epsilon = 0; |
---|
| 808 | LargeCost lc; |
---|
| 809 | for (int i = 0; i != _root; ++i) { |
---|
| 810 | last_out = _first_out[i+1]; |
---|
| 811 | for (int j = _first_out[i]; j != last_out; ++j) { |
---|
| 812 | lc = static_cast<LargeCost>(_scost[j]) * _res_node_num * _alpha; |
---|
| 813 | _cost[j] = lc; |
---|
| 814 | if (lc > _epsilon) _epsilon = lc; |
---|
| 815 | } |
---|
| 816 | } |
---|
| 817 | _epsilon /= _alpha; |
---|
[874] | 818 | |
---|
[875] | 819 | // Initialize maps for Circulation and remove non-zero lower bounds |
---|
| 820 | ConstMap<Arc, Value> low(0); |
---|
| 821 | typedef typename Digraph::template ArcMap<Value> ValueArcMap; |
---|
| 822 | typedef typename Digraph::template NodeMap<Value> ValueNodeMap; |
---|
| 823 | ValueArcMap cap(_graph), flow(_graph); |
---|
| 824 | ValueNodeMap sup(_graph); |
---|
| 825 | for (NodeIt n(_graph); n != INVALID; ++n) { |
---|
| 826 | sup[n] = _supply[_node_id[n]]; |
---|
[874] | 827 | } |
---|
[875] | 828 | if (_have_lower) { |
---|
| 829 | for (ArcIt a(_graph); a != INVALID; ++a) { |
---|
| 830 | int j = _arc_idf[a]; |
---|
| 831 | Value c = _lower[j]; |
---|
| 832 | cap[a] = _upper[j] - c; |
---|
| 833 | sup[_graph.source(a)] -= c; |
---|
| 834 | sup[_graph.target(a)] += c; |
---|
| 835 | } |
---|
| 836 | } else { |
---|
| 837 | for (ArcIt a(_graph); a != INVALID; ++a) { |
---|
| 838 | cap[a] = _upper[_arc_idf[a]]; |
---|
| 839 | } |
---|
| 840 | } |
---|
[874] | 841 | |
---|
[910] | 842 | _sup_node_num = 0; |
---|
| 843 | for (NodeIt n(_graph); n != INVALID; ++n) { |
---|
| 844 | if (sup[n] > 0) ++_sup_node_num; |
---|
| 845 | } |
---|
| 846 | |
---|
[874] | 847 | // Find a feasible flow using Circulation |
---|
[875] | 848 | Circulation<Digraph, ConstMap<Arc, Value>, ValueArcMap, ValueNodeMap> |
---|
| 849 | circ(_graph, low, cap, sup); |
---|
| 850 | if (!circ.flowMap(flow).run()) return INFEASIBLE; |
---|
| 851 | |
---|
| 852 | // Set residual capacities and handle GEQ supply type |
---|
| 853 | if (_sum_supply < 0) { |
---|
| 854 | for (ArcIt a(_graph); a != INVALID; ++a) { |
---|
| 855 | Value fa = flow[a]; |
---|
| 856 | _res_cap[_arc_idf[a]] = cap[a] - fa; |
---|
| 857 | _res_cap[_arc_idb[a]] = fa; |
---|
| 858 | sup[_graph.source(a)] -= fa; |
---|
| 859 | sup[_graph.target(a)] += fa; |
---|
| 860 | } |
---|
| 861 | for (NodeIt n(_graph); n != INVALID; ++n) { |
---|
| 862 | _excess[_node_id[n]] = sup[n]; |
---|
| 863 | } |
---|
| 864 | for (int a = _first_out[_root]; a != _res_arc_num; ++a) { |
---|
| 865 | int u = _target[a]; |
---|
| 866 | int ra = _reverse[a]; |
---|
| 867 | _res_cap[a] = -_sum_supply + 1; |
---|
| 868 | _res_cap[ra] = -_excess[u]; |
---|
| 869 | _cost[a] = 0; |
---|
| 870 | _cost[ra] = 0; |
---|
| 871 | _excess[u] = 0; |
---|
| 872 | } |
---|
| 873 | } else { |
---|
| 874 | for (ArcIt a(_graph); a != INVALID; ++a) { |
---|
| 875 | Value fa = flow[a]; |
---|
| 876 | _res_cap[_arc_idf[a]] = cap[a] - fa; |
---|
| 877 | _res_cap[_arc_idb[a]] = fa; |
---|
| 878 | } |
---|
| 879 | for (int a = _first_out[_root]; a != _res_arc_num; ++a) { |
---|
| 880 | int ra = _reverse[a]; |
---|
[910] | 881 | _res_cap[a] = 0; |
---|
[875] | 882 | _res_cap[ra] = 0; |
---|
| 883 | _cost[a] = 0; |
---|
| 884 | _cost[ra] = 0; |
---|
| 885 | } |
---|
| 886 | } |
---|
[956] | 887 | |
---|
| 888 | // Initialize data structures for buckets |
---|
[910] | 889 | _max_rank = _alpha * _res_node_num; |
---|
| 890 | _buckets.resize(_max_rank); |
---|
| 891 | _bucket_next.resize(_res_node_num + 1); |
---|
| 892 | _bucket_prev.resize(_res_node_num + 1); |
---|
| 893 | _rank.resize(_res_node_num + 1); |
---|
[956] | 894 | |
---|
[1045] | 895 | return OPTIMAL; |
---|
| 896 | } |
---|
| 897 | |
---|
| 898 | // Execute the algorithm and transform the results |
---|
| 899 | void start(Method method) { |
---|
| 900 | const int MAX_PARTIAL_PATH_LENGTH = 4; |
---|
| 901 | |
---|
[876] | 902 | switch (method) { |
---|
| 903 | case PUSH: |
---|
| 904 | startPush(); |
---|
| 905 | break; |
---|
| 906 | case AUGMENT: |
---|
[1041] | 907 | startAugment(_res_node_num - 1); |
---|
[876] | 908 | break; |
---|
| 909 | case PARTIAL_AUGMENT: |
---|
[1045] | 910 | startAugment(MAX_PARTIAL_PATH_LENGTH); |
---|
[876] | 911 | break; |
---|
[875] | 912 | } |
---|
| 913 | |
---|
[1048] | 914 | // Compute node potentials (dual solution) |
---|
| 915 | for (int i = 0; i != _res_node_num; ++i) { |
---|
| 916 | _pi[i] = static_cast<Cost>(_pi[i] / (_res_node_num * _alpha)); |
---|
| 917 | } |
---|
| 918 | bool optimal = true; |
---|
| 919 | for (int i = 0; optimal && i != _res_node_num; ++i) { |
---|
| 920 | LargeCost pi_i = _pi[i]; |
---|
| 921 | int last_out = _first_out[i+1]; |
---|
| 922 | for (int j = _first_out[i]; j != last_out; ++j) { |
---|
| 923 | if (_res_cap[j] > 0 && _scost[j] + pi_i - _pi[_target[j]] < 0) { |
---|
| 924 | optimal = false; |
---|
| 925 | break; |
---|
| 926 | } |
---|
[875] | 927 | } |
---|
| 928 | } |
---|
| 929 | |
---|
[1048] | 930 | if (!optimal) { |
---|
| 931 | // Compute node potentials for the original costs with BellmanFord |
---|
| 932 | // (if it is necessary) |
---|
| 933 | typedef std::pair<int, int> IntPair; |
---|
| 934 | StaticDigraph sgr; |
---|
| 935 | std::vector<IntPair> arc_vec; |
---|
| 936 | std::vector<LargeCost> cost_vec; |
---|
| 937 | LargeCostArcMap cost_map(cost_vec); |
---|
| 938 | |
---|
| 939 | arc_vec.clear(); |
---|
| 940 | cost_vec.clear(); |
---|
| 941 | for (int j = 0; j != _res_arc_num; ++j) { |
---|
| 942 | if (_res_cap[j] > 0) { |
---|
| 943 | int u = _source[j], v = _target[j]; |
---|
| 944 | arc_vec.push_back(IntPair(u, v)); |
---|
| 945 | cost_vec.push_back(_scost[j] + _pi[u] - _pi[v]); |
---|
| 946 | } |
---|
| 947 | } |
---|
| 948 | sgr.build(_res_node_num, arc_vec.begin(), arc_vec.end()); |
---|
| 949 | |
---|
| 950 | typename BellmanFord<StaticDigraph, LargeCostArcMap>::Create |
---|
| 951 | bf(sgr, cost_map); |
---|
| 952 | bf.init(0); |
---|
| 953 | bf.start(); |
---|
| 954 | |
---|
| 955 | for (int i = 0; i != _res_node_num; ++i) { |
---|
| 956 | _pi[i] += bf.dist(sgr.node(i)); |
---|
| 957 | } |
---|
| 958 | } |
---|
| 959 | |
---|
| 960 | // Shift potentials to meet the requirements of the GEQ type |
---|
| 961 | // optimality conditions |
---|
| 962 | LargeCost max_pot = _pi[_root]; |
---|
| 963 | for (int i = 0; i != _res_node_num; ++i) { |
---|
| 964 | if (_pi[i] > max_pot) max_pot = _pi[i]; |
---|
| 965 | } |
---|
| 966 | if (max_pot != 0) { |
---|
| 967 | for (int i = 0; i != _res_node_num; ++i) { |
---|
| 968 | _pi[i] -= max_pot; |
---|
| 969 | } |
---|
| 970 | } |
---|
[875] | 971 | |
---|
| 972 | // Handle non-zero lower bounds |
---|
| 973 | if (_have_lower) { |
---|
| 974 | int limit = _first_out[_root]; |
---|
| 975 | for (int j = 0; j != limit; ++j) { |
---|
| 976 | if (!_forward[j]) _res_cap[j] += _lower[j]; |
---|
| 977 | } |
---|
| 978 | } |
---|
[874] | 979 | } |
---|
[956] | 980 | |
---|
[910] | 981 | // Initialize a cost scaling phase |
---|
| 982 | void initPhase() { |
---|
| 983 | // Saturate arcs not satisfying the optimality condition |
---|
| 984 | for (int u = 0; u != _res_node_num; ++u) { |
---|
| 985 | int last_out = _first_out[u+1]; |
---|
| 986 | LargeCost pi_u = _pi[u]; |
---|
| 987 | for (int a = _first_out[u]; a != last_out; ++a) { |
---|
[1045] | 988 | Value delta = _res_cap[a]; |
---|
| 989 | if (delta > 0) { |
---|
| 990 | int v = _target[a]; |
---|
| 991 | if (_cost[a] + pi_u - _pi[v] < 0) { |
---|
| 992 | _excess[u] -= delta; |
---|
| 993 | _excess[v] += delta; |
---|
| 994 | _res_cap[a] = 0; |
---|
| 995 | _res_cap[_reverse[a]] += delta; |
---|
| 996 | } |
---|
[910] | 997 | } |
---|
| 998 | } |
---|
| 999 | } |
---|
[956] | 1000 | |
---|
[910] | 1001 | // Find active nodes (i.e. nodes with positive excess) |
---|
| 1002 | for (int u = 0; u != _res_node_num; ++u) { |
---|
| 1003 | if (_excess[u] > 0) _active_nodes.push_back(u); |
---|
| 1004 | } |
---|
| 1005 | |
---|
| 1006 | // Initialize the next arcs |
---|
| 1007 | for (int u = 0; u != _res_node_num; ++u) { |
---|
| 1008 | _next_out[u] = _first_out[u]; |
---|
| 1009 | } |
---|
| 1010 | } |
---|
[956] | 1011 | |
---|
[1047] | 1012 | // Price (potential) refinement heuristic |
---|
| 1013 | bool priceRefinement() { |
---|
[910] | 1014 | |
---|
[1047] | 1015 | // Stack for stroing the topological order |
---|
| 1016 | IntVector stack(_res_node_num); |
---|
| 1017 | int stack_top; |
---|
| 1018 | |
---|
| 1019 | // Perform phases |
---|
| 1020 | while (topologicalSort(stack, stack_top)) { |
---|
| 1021 | |
---|
| 1022 | // Compute node ranks in the acyclic admissible network and |
---|
| 1023 | // store the nodes in buckets |
---|
| 1024 | for (int i = 0; i != _res_node_num; ++i) { |
---|
| 1025 | _rank[i] = 0; |
---|
[910] | 1026 | } |
---|
[1047] | 1027 | const int bucket_end = _root + 1; |
---|
| 1028 | for (int r = 0; r != _max_rank; ++r) { |
---|
| 1029 | _buckets[r] = bucket_end; |
---|
| 1030 | } |
---|
| 1031 | int top_rank = 0; |
---|
| 1032 | for ( ; stack_top >= 0; --stack_top) { |
---|
| 1033 | int u = stack[stack_top], v; |
---|
| 1034 | int rank_u = _rank[u]; |
---|
| 1035 | |
---|
| 1036 | LargeCost rc, pi_u = _pi[u]; |
---|
| 1037 | int last_out = _first_out[u+1]; |
---|
| 1038 | for (int a = _first_out[u]; a != last_out; ++a) { |
---|
| 1039 | if (_res_cap[a] > 0) { |
---|
| 1040 | v = _target[a]; |
---|
| 1041 | rc = _cost[a] + pi_u - _pi[v]; |
---|
| 1042 | if (rc < 0) { |
---|
| 1043 | LargeCost nrc = static_cast<LargeCost>((-rc - 0.5) / _epsilon); |
---|
| 1044 | if (nrc < LargeCost(_max_rank)) { |
---|
| 1045 | int new_rank_v = rank_u + static_cast<int>(nrc); |
---|
| 1046 | if (new_rank_v > _rank[v]) { |
---|
| 1047 | _rank[v] = new_rank_v; |
---|
| 1048 | } |
---|
| 1049 | } |
---|
| 1050 | } |
---|
| 1051 | } |
---|
| 1052 | } |
---|
| 1053 | |
---|
| 1054 | if (rank_u > 0) { |
---|
| 1055 | top_rank = std::max(top_rank, rank_u); |
---|
| 1056 | int bfirst = _buckets[rank_u]; |
---|
| 1057 | _bucket_next[u] = bfirst; |
---|
| 1058 | _bucket_prev[bfirst] = u; |
---|
| 1059 | _buckets[rank_u] = u; |
---|
| 1060 | } |
---|
| 1061 | } |
---|
| 1062 | |
---|
| 1063 | // Check if the current flow is epsilon-optimal |
---|
| 1064 | if (top_rank == 0) { |
---|
| 1065 | return true; |
---|
| 1066 | } |
---|
| 1067 | |
---|
| 1068 | // Process buckets in top-down order |
---|
| 1069 | for (int rank = top_rank; rank > 0; --rank) { |
---|
| 1070 | while (_buckets[rank] != bucket_end) { |
---|
| 1071 | // Remove the first node from the current bucket |
---|
| 1072 | int u = _buckets[rank]; |
---|
| 1073 | _buckets[rank] = _bucket_next[u]; |
---|
| 1074 | |
---|
| 1075 | // Search the outgoing arcs of u |
---|
| 1076 | LargeCost rc, pi_u = _pi[u]; |
---|
| 1077 | int last_out = _first_out[u+1]; |
---|
| 1078 | int v, old_rank_v, new_rank_v; |
---|
| 1079 | for (int a = _first_out[u]; a != last_out; ++a) { |
---|
| 1080 | if (_res_cap[a] > 0) { |
---|
| 1081 | v = _target[a]; |
---|
| 1082 | old_rank_v = _rank[v]; |
---|
| 1083 | |
---|
| 1084 | if (old_rank_v < rank) { |
---|
| 1085 | |
---|
| 1086 | // Compute the new rank of node v |
---|
| 1087 | rc = _cost[a] + pi_u - _pi[v]; |
---|
| 1088 | if (rc < 0) { |
---|
| 1089 | new_rank_v = rank; |
---|
| 1090 | } else { |
---|
| 1091 | LargeCost nrc = rc / _epsilon; |
---|
| 1092 | new_rank_v = 0; |
---|
| 1093 | if (nrc < LargeCost(_max_rank)) { |
---|
| 1094 | new_rank_v = rank - 1 - static_cast<int>(nrc); |
---|
| 1095 | } |
---|
| 1096 | } |
---|
| 1097 | |
---|
| 1098 | // Change the rank of node v |
---|
| 1099 | if (new_rank_v > old_rank_v) { |
---|
| 1100 | _rank[v] = new_rank_v; |
---|
| 1101 | |
---|
| 1102 | // Remove v from its old bucket |
---|
| 1103 | if (old_rank_v > 0) { |
---|
| 1104 | if (_buckets[old_rank_v] == v) { |
---|
| 1105 | _buckets[old_rank_v] = _bucket_next[v]; |
---|
| 1106 | } else { |
---|
| 1107 | int pv = _bucket_prev[v], nv = _bucket_next[v]; |
---|
| 1108 | _bucket_next[pv] = nv; |
---|
| 1109 | _bucket_prev[nv] = pv; |
---|
| 1110 | } |
---|
| 1111 | } |
---|
| 1112 | |
---|
| 1113 | // Insert v into its new bucket |
---|
| 1114 | int nv = _buckets[new_rank_v]; |
---|
| 1115 | _bucket_next[v] = nv; |
---|
| 1116 | _bucket_prev[nv] = v; |
---|
| 1117 | _buckets[new_rank_v] = v; |
---|
| 1118 | } |
---|
| 1119 | } |
---|
| 1120 | } |
---|
| 1121 | } |
---|
| 1122 | |
---|
| 1123 | // Refine potential of node u |
---|
| 1124 | _pi[u] -= rank * _epsilon; |
---|
| 1125 | } |
---|
| 1126 | } |
---|
| 1127 | |
---|
[910] | 1128 | } |
---|
| 1129 | |
---|
[1047] | 1130 | return false; |
---|
| 1131 | } |
---|
| 1132 | |
---|
| 1133 | // Find and cancel cycles in the admissible network and |
---|
| 1134 | // determine topological order using DFS |
---|
| 1135 | bool topologicalSort(IntVector &stack, int &stack_top) { |
---|
| 1136 | const int MAX_CYCLE_CANCEL = 1; |
---|
| 1137 | |
---|
| 1138 | BoolVector reached(_res_node_num, false); |
---|
| 1139 | BoolVector processed(_res_node_num, false); |
---|
| 1140 | IntVector pred(_res_node_num); |
---|
| 1141 | for (int i = 0; i != _res_node_num; ++i) { |
---|
| 1142 | _next_out[i] = _first_out[i]; |
---|
[910] | 1143 | } |
---|
[1047] | 1144 | stack_top = -1; |
---|
| 1145 | |
---|
| 1146 | int cycle_cnt = 0; |
---|
| 1147 | for (int start = 0; start != _res_node_num; ++start) { |
---|
| 1148 | if (reached[start]) continue; |
---|
| 1149 | |
---|
| 1150 | // Start DFS search from this start node |
---|
| 1151 | pred[start] = -1; |
---|
| 1152 | int tip = start, v; |
---|
| 1153 | while (true) { |
---|
| 1154 | // Check the outgoing arcs of the current tip node |
---|
| 1155 | reached[tip] = true; |
---|
| 1156 | LargeCost pi_tip = _pi[tip]; |
---|
| 1157 | int a, last_out = _first_out[tip+1]; |
---|
| 1158 | for (a = _next_out[tip]; a != last_out; ++a) { |
---|
| 1159 | if (_res_cap[a] > 0) { |
---|
| 1160 | v = _target[a]; |
---|
| 1161 | if (_cost[a] + pi_tip - _pi[v] < 0) { |
---|
| 1162 | if (!reached[v]) { |
---|
| 1163 | // A new node is reached |
---|
| 1164 | reached[v] = true; |
---|
| 1165 | pred[v] = tip; |
---|
| 1166 | _next_out[tip] = a; |
---|
| 1167 | tip = v; |
---|
| 1168 | a = _next_out[tip]; |
---|
| 1169 | last_out = _first_out[tip+1]; |
---|
| 1170 | break; |
---|
| 1171 | } |
---|
| 1172 | else if (!processed[v]) { |
---|
| 1173 | // A cycle is found |
---|
| 1174 | ++cycle_cnt; |
---|
| 1175 | _next_out[tip] = a; |
---|
| 1176 | |
---|
| 1177 | // Find the minimum residual capacity along the cycle |
---|
| 1178 | Value d, delta = _res_cap[a]; |
---|
| 1179 | int u, delta_node = tip; |
---|
| 1180 | for (u = tip; u != v; ) { |
---|
| 1181 | u = pred[u]; |
---|
| 1182 | d = _res_cap[_next_out[u]]; |
---|
| 1183 | if (d <= delta) { |
---|
| 1184 | delta = d; |
---|
| 1185 | delta_node = u; |
---|
| 1186 | } |
---|
| 1187 | } |
---|
| 1188 | |
---|
| 1189 | // Augment along the cycle |
---|
| 1190 | _res_cap[a] -= delta; |
---|
| 1191 | _res_cap[_reverse[a]] += delta; |
---|
| 1192 | for (u = tip; u != v; ) { |
---|
| 1193 | u = pred[u]; |
---|
| 1194 | int ca = _next_out[u]; |
---|
| 1195 | _res_cap[ca] -= delta; |
---|
| 1196 | _res_cap[_reverse[ca]] += delta; |
---|
| 1197 | } |
---|
| 1198 | |
---|
| 1199 | // Check the maximum number of cycle canceling |
---|
| 1200 | if (cycle_cnt >= MAX_CYCLE_CANCEL) { |
---|
| 1201 | return false; |
---|
| 1202 | } |
---|
| 1203 | |
---|
| 1204 | // Roll back search to delta_node |
---|
| 1205 | if (delta_node != tip) { |
---|
| 1206 | for (u = tip; u != delta_node; u = pred[u]) { |
---|
| 1207 | reached[u] = false; |
---|
| 1208 | } |
---|
| 1209 | tip = delta_node; |
---|
| 1210 | a = _next_out[tip] + 1; |
---|
| 1211 | last_out = _first_out[tip+1]; |
---|
| 1212 | break; |
---|
| 1213 | } |
---|
| 1214 | } |
---|
| 1215 | } |
---|
| 1216 | } |
---|
| 1217 | } |
---|
| 1218 | |
---|
| 1219 | // Step back to the previous node |
---|
| 1220 | if (a == last_out) { |
---|
| 1221 | processed[tip] = true; |
---|
| 1222 | stack[++stack_top] = tip; |
---|
| 1223 | tip = pred[tip]; |
---|
| 1224 | if (tip < 0) { |
---|
| 1225 | // Finish DFS from the current start node |
---|
| 1226 | break; |
---|
| 1227 | } |
---|
| 1228 | ++_next_out[tip]; |
---|
| 1229 | } |
---|
| 1230 | } |
---|
| 1231 | |
---|
| 1232 | } |
---|
| 1233 | |
---|
| 1234 | return (cycle_cnt == 0); |
---|
[910] | 1235 | } |
---|
| 1236 | |
---|
| 1237 | // Global potential update heuristic |
---|
| 1238 | void globalUpdate() { |
---|
[1045] | 1239 | const int bucket_end = _root + 1; |
---|
[956] | 1240 | |
---|
[910] | 1241 | // Initialize buckets |
---|
| 1242 | for (int r = 0; r != _max_rank; ++r) { |
---|
| 1243 | _buckets[r] = bucket_end; |
---|
| 1244 | } |
---|
| 1245 | Value total_excess = 0; |
---|
[1045] | 1246 | int b0 = bucket_end; |
---|
[910] | 1247 | for (int i = 0; i != _res_node_num; ++i) { |
---|
| 1248 | if (_excess[i] < 0) { |
---|
| 1249 | _rank[i] = 0; |
---|
[1045] | 1250 | _bucket_next[i] = b0; |
---|
| 1251 | _bucket_prev[b0] = i; |
---|
| 1252 | b0 = i; |
---|
[910] | 1253 | } else { |
---|
| 1254 | total_excess += _excess[i]; |
---|
| 1255 | _rank[i] = _max_rank; |
---|
| 1256 | } |
---|
| 1257 | } |
---|
| 1258 | if (total_excess == 0) return; |
---|
[1045] | 1259 | _buckets[0] = b0; |
---|
[910] | 1260 | |
---|
| 1261 | // Search the buckets |
---|
| 1262 | int r = 0; |
---|
| 1263 | for ( ; r != _max_rank; ++r) { |
---|
| 1264 | while (_buckets[r] != bucket_end) { |
---|
| 1265 | // Remove the first node from the current bucket |
---|
| 1266 | int u = _buckets[r]; |
---|
| 1267 | _buckets[r] = _bucket_next[u]; |
---|
[956] | 1268 | |
---|
[910] | 1269 | // Search the incomming arcs of u |
---|
| 1270 | LargeCost pi_u = _pi[u]; |
---|
| 1271 | int last_out = _first_out[u+1]; |
---|
| 1272 | for (int a = _first_out[u]; a != last_out; ++a) { |
---|
| 1273 | int ra = _reverse[a]; |
---|
| 1274 | if (_res_cap[ra] > 0) { |
---|
| 1275 | int v = _source[ra]; |
---|
| 1276 | int old_rank_v = _rank[v]; |
---|
| 1277 | if (r < old_rank_v) { |
---|
| 1278 | // Compute the new rank of v |
---|
| 1279 | LargeCost nrc = (_cost[ra] + _pi[v] - pi_u) / _epsilon; |
---|
| 1280 | int new_rank_v = old_rank_v; |
---|
[1045] | 1281 | if (nrc < LargeCost(_max_rank)) { |
---|
| 1282 | new_rank_v = r + 1 + static_cast<int>(nrc); |
---|
| 1283 | } |
---|
[956] | 1284 | |
---|
[910] | 1285 | // Change the rank of v |
---|
| 1286 | if (new_rank_v < old_rank_v) { |
---|
| 1287 | _rank[v] = new_rank_v; |
---|
| 1288 | _next_out[v] = _first_out[v]; |
---|
[956] | 1289 | |
---|
[910] | 1290 | // Remove v from its old bucket |
---|
| 1291 | if (old_rank_v < _max_rank) { |
---|
| 1292 | if (_buckets[old_rank_v] == v) { |
---|
| 1293 | _buckets[old_rank_v] = _bucket_next[v]; |
---|
| 1294 | } else { |
---|
[1045] | 1295 | int pv = _bucket_prev[v], nv = _bucket_next[v]; |
---|
| 1296 | _bucket_next[pv] = nv; |
---|
| 1297 | _bucket_prev[nv] = pv; |
---|
[910] | 1298 | } |
---|
| 1299 | } |
---|
[956] | 1300 | |
---|
[1045] | 1301 | // Insert v into its new bucket |
---|
| 1302 | int nv = _buckets[new_rank_v]; |
---|
| 1303 | _bucket_next[v] = nv; |
---|
| 1304 | _bucket_prev[nv] = v; |
---|
[910] | 1305 | _buckets[new_rank_v] = v; |
---|
| 1306 | } |
---|
| 1307 | } |
---|
| 1308 | } |
---|
| 1309 | } |
---|
| 1310 | |
---|
| 1311 | // Finish search if there are no more active nodes |
---|
| 1312 | if (_excess[u] > 0) { |
---|
| 1313 | total_excess -= _excess[u]; |
---|
| 1314 | if (total_excess <= 0) break; |
---|
| 1315 | } |
---|
| 1316 | } |
---|
| 1317 | if (total_excess <= 0) break; |
---|
| 1318 | } |
---|
[956] | 1319 | |
---|
[910] | 1320 | // Relabel nodes |
---|
| 1321 | for (int u = 0; u != _res_node_num; ++u) { |
---|
| 1322 | int k = std::min(_rank[u], r); |
---|
| 1323 | if (k > 0) { |
---|
| 1324 | _pi[u] -= _epsilon * k; |
---|
| 1325 | _next_out[u] = _first_out[u]; |
---|
| 1326 | } |
---|
| 1327 | } |
---|
| 1328 | } |
---|
[874] | 1329 | |
---|
[876] | 1330 | /// Execute the algorithm performing augment and relabel operations |
---|
[1041] | 1331 | void startAugment(int max_length) { |
---|
[874] | 1332 | // Paramters for heuristics |
---|
[1047] | 1333 | const int PRICE_REFINEMENT_LIMIT = 2; |
---|
[1046] | 1334 | const double GLOBAL_UPDATE_FACTOR = 1.0; |
---|
| 1335 | const int global_update_skip = static_cast<int>(GLOBAL_UPDATE_FACTOR * |
---|
[910] | 1336 | (_res_node_num + _sup_node_num * _sup_node_num)); |
---|
[1046] | 1337 | int next_global_update_limit = global_update_skip; |
---|
[956] | 1338 | |
---|
[875] | 1339 | // Perform cost scaling phases |
---|
[1046] | 1340 | IntVector path; |
---|
| 1341 | BoolVector path_arc(_res_arc_num, false); |
---|
| 1342 | int relabel_cnt = 0; |
---|
[1047] | 1343 | int eps_phase_cnt = 0; |
---|
[874] | 1344 | for ( ; _epsilon >= 1; _epsilon = _epsilon < _alpha && _epsilon > 1 ? |
---|
| 1345 | 1 : _epsilon / _alpha ) |
---|
| 1346 | { |
---|
[1047] | 1347 | ++eps_phase_cnt; |
---|
| 1348 | |
---|
| 1349 | // Price refinement heuristic |
---|
| 1350 | if (eps_phase_cnt >= PRICE_REFINEMENT_LIMIT) { |
---|
| 1351 | if (priceRefinement()) continue; |
---|
[874] | 1352 | } |
---|
[956] | 1353 | |
---|
[910] | 1354 | // Initialize current phase |
---|
| 1355 | initPhase(); |
---|
[956] | 1356 | |
---|
[874] | 1357 | // Perform partial augment and relabel operations |
---|
[875] | 1358 | while (true) { |
---|
[874] | 1359 | // Select an active node (FIFO selection) |
---|
[875] | 1360 | while (_active_nodes.size() > 0 && |
---|
| 1361 | _excess[_active_nodes.front()] <= 0) { |
---|
| 1362 | _active_nodes.pop_front(); |
---|
[874] | 1363 | } |
---|
[875] | 1364 | if (_active_nodes.size() == 0) break; |
---|
| 1365 | int start = _active_nodes.front(); |
---|
[874] | 1366 | |
---|
| 1367 | // Find an augmenting path from the start node |
---|
[875] | 1368 | int tip = start; |
---|
[1046] | 1369 | while (int(path.size()) < max_length && _excess[tip] >= 0) { |
---|
[875] | 1370 | int u; |
---|
[1046] | 1371 | LargeCost rc, min_red_cost = std::numeric_limits<LargeCost>::max(); |
---|
| 1372 | LargeCost pi_tip = _pi[tip]; |
---|
[910] | 1373 | int last_out = _first_out[tip+1]; |
---|
[875] | 1374 | for (int a = _next_out[tip]; a != last_out; ++a) { |
---|
[1046] | 1375 | if (_res_cap[a] > 0) { |
---|
| 1376 | u = _target[a]; |
---|
| 1377 | rc = _cost[a] + pi_tip - _pi[u]; |
---|
| 1378 | if (rc < 0) { |
---|
| 1379 | path.push_back(a); |
---|
| 1380 | _next_out[tip] = a; |
---|
| 1381 | if (path_arc[a]) { |
---|
| 1382 | goto augment; // a cycle is found, stop path search |
---|
| 1383 | } |
---|
| 1384 | tip = u; |
---|
| 1385 | path_arc[a] = true; |
---|
| 1386 | goto next_step; |
---|
| 1387 | } |
---|
| 1388 | else if (rc < min_red_cost) { |
---|
| 1389 | min_red_cost = rc; |
---|
| 1390 | } |
---|
[874] | 1391 | } |
---|
| 1392 | } |
---|
| 1393 | |
---|
| 1394 | // Relabel tip node |
---|
[910] | 1395 | if (tip != start) { |
---|
| 1396 | int ra = _reverse[path.back()]; |
---|
[1046] | 1397 | min_red_cost = |
---|
| 1398 | std::min(min_red_cost, _cost[ra] + pi_tip - _pi[_target[ra]]); |
---|
[910] | 1399 | } |
---|
[1046] | 1400 | last_out = _next_out[tip]; |
---|
[875] | 1401 | for (int a = _first_out[tip]; a != last_out; ++a) { |
---|
[1046] | 1402 | if (_res_cap[a] > 0) { |
---|
| 1403 | rc = _cost[a] + pi_tip - _pi[_target[a]]; |
---|
| 1404 | if (rc < min_red_cost) { |
---|
| 1405 | min_red_cost = rc; |
---|
| 1406 | } |
---|
[875] | 1407 | } |
---|
[874] | 1408 | } |
---|
[875] | 1409 | _pi[tip] -= min_red_cost + _epsilon; |
---|
| 1410 | _next_out[tip] = _first_out[tip]; |
---|
[910] | 1411 | ++relabel_cnt; |
---|
[874] | 1412 | |
---|
| 1413 | // Step back |
---|
| 1414 | if (tip != start) { |
---|
[1046] | 1415 | int pa = path.back(); |
---|
| 1416 | path_arc[pa] = false; |
---|
| 1417 | tip = _source[pa]; |
---|
[910] | 1418 | path.pop_back(); |
---|
[874] | 1419 | } |
---|
| 1420 | |
---|
[875] | 1421 | next_step: ; |
---|
[874] | 1422 | } |
---|
| 1423 | |
---|
| 1424 | // Augment along the found path (as much flow as possible) |
---|
[1046] | 1425 | augment: |
---|
[875] | 1426 | Value delta; |
---|
[910] | 1427 | int pa, u, v = start; |
---|
| 1428 | for (int i = 0; i != int(path.size()); ++i) { |
---|
| 1429 | pa = path[i]; |
---|
[875] | 1430 | u = v; |
---|
[910] | 1431 | v = _target[pa]; |
---|
[1046] | 1432 | path_arc[pa] = false; |
---|
[875] | 1433 | delta = std::min(_res_cap[pa], _excess[u]); |
---|
| 1434 | _res_cap[pa] -= delta; |
---|
| 1435 | _res_cap[_reverse[pa]] += delta; |
---|
| 1436 | _excess[u] -= delta; |
---|
| 1437 | _excess[v] += delta; |
---|
[1046] | 1438 | if (_excess[v] > 0 && _excess[v] <= delta) { |
---|
[875] | 1439 | _active_nodes.push_back(v); |
---|
[1046] | 1440 | } |
---|
[874] | 1441 | } |
---|
[1046] | 1442 | path.clear(); |
---|
[910] | 1443 | |
---|
| 1444 | // Global update heuristic |
---|
[1046] | 1445 | if (relabel_cnt >= next_global_update_limit) { |
---|
[910] | 1446 | globalUpdate(); |
---|
[1046] | 1447 | next_global_update_limit += global_update_skip; |
---|
[910] | 1448 | } |
---|
[874] | 1449 | } |
---|
[1046] | 1450 | |
---|
[874] | 1451 | } |
---|
[1046] | 1452 | |
---|
[874] | 1453 | } |
---|
| 1454 | |
---|
[875] | 1455 | /// Execute the algorithm performing push and relabel operations |
---|
[876] | 1456 | void startPush() { |
---|
[874] | 1457 | // Paramters for heuristics |
---|
[1047] | 1458 | const int PRICE_REFINEMENT_LIMIT = 2; |
---|
[910] | 1459 | const double GLOBAL_UPDATE_FACTOR = 2.0; |
---|
[874] | 1460 | |
---|
[1046] | 1461 | const int global_update_skip = static_cast<int>(GLOBAL_UPDATE_FACTOR * |
---|
[910] | 1462 | (_res_node_num + _sup_node_num * _sup_node_num)); |
---|
[1046] | 1463 | int next_global_update_limit = global_update_skip; |
---|
[956] | 1464 | |
---|
[875] | 1465 | // Perform cost scaling phases |
---|
| 1466 | BoolVector hyper(_res_node_num, false); |
---|
[910] | 1467 | LargeCostVector hyper_cost(_res_node_num); |
---|
[1046] | 1468 | int relabel_cnt = 0; |
---|
[1047] | 1469 | int eps_phase_cnt = 0; |
---|
[874] | 1470 | for ( ; _epsilon >= 1; _epsilon = _epsilon < _alpha && _epsilon > 1 ? |
---|
| 1471 | 1 : _epsilon / _alpha ) |
---|
| 1472 | { |
---|
[1047] | 1473 | ++eps_phase_cnt; |
---|
| 1474 | |
---|
| 1475 | // Price refinement heuristic |
---|
| 1476 | if (eps_phase_cnt >= PRICE_REFINEMENT_LIMIT) { |
---|
| 1477 | if (priceRefinement()) continue; |
---|
[874] | 1478 | } |
---|
[956] | 1479 | |
---|
[910] | 1480 | // Initialize current phase |
---|
| 1481 | initPhase(); |
---|
[874] | 1482 | |
---|
| 1483 | // Perform push and relabel operations |
---|
[875] | 1484 | while (_active_nodes.size() > 0) { |
---|
[910] | 1485 | LargeCost min_red_cost, rc, pi_n; |
---|
[875] | 1486 | Value delta; |
---|
| 1487 | int n, t, a, last_out = _res_arc_num; |
---|
| 1488 | |
---|
[910] | 1489 | next_node: |
---|
[874] | 1490 | // Select an active node (FIFO selection) |
---|
[875] | 1491 | n = _active_nodes.front(); |
---|
[910] | 1492 | last_out = _first_out[n+1]; |
---|
| 1493 | pi_n = _pi[n]; |
---|
[956] | 1494 | |
---|
[874] | 1495 | // Perform push operations if there are admissible arcs |
---|
[875] | 1496 | if (_excess[n] > 0) { |
---|
| 1497 | for (a = _next_out[n]; a != last_out; ++a) { |
---|
| 1498 | if (_res_cap[a] > 0 && |
---|
[910] | 1499 | _cost[a] + pi_n - _pi[_target[a]] < 0) { |
---|
[875] | 1500 | delta = std::min(_res_cap[a], _excess[n]); |
---|
| 1501 | t = _target[a]; |
---|
[874] | 1502 | |
---|
| 1503 | // Push-look-ahead heuristic |
---|
[875] | 1504 | Value ahead = -_excess[t]; |
---|
[910] | 1505 | int last_out_t = _first_out[t+1]; |
---|
| 1506 | LargeCost pi_t = _pi[t]; |
---|
[875] | 1507 | for (int ta = _next_out[t]; ta != last_out_t; ++ta) { |
---|
[956] | 1508 | if (_res_cap[ta] > 0 && |
---|
[910] | 1509 | _cost[ta] + pi_t - _pi[_target[ta]] < 0) |
---|
[875] | 1510 | ahead += _res_cap[ta]; |
---|
| 1511 | if (ahead >= delta) break; |
---|
[874] | 1512 | } |
---|
| 1513 | if (ahead < 0) ahead = 0; |
---|
| 1514 | |
---|
| 1515 | // Push flow along the arc |
---|
[910] | 1516 | if (ahead < delta && !hyper[t]) { |
---|
[875] | 1517 | _res_cap[a] -= ahead; |
---|
| 1518 | _res_cap[_reverse[a]] += ahead; |
---|
[874] | 1519 | _excess[n] -= ahead; |
---|
| 1520 | _excess[t] += ahead; |
---|
[875] | 1521 | _active_nodes.push_front(t); |
---|
[874] | 1522 | hyper[t] = true; |
---|
[910] | 1523 | hyper_cost[t] = _cost[a] + pi_n - pi_t; |
---|
[875] | 1524 | _next_out[n] = a; |
---|
| 1525 | goto next_node; |
---|
[874] | 1526 | } else { |
---|
[875] | 1527 | _res_cap[a] -= delta; |
---|
| 1528 | _res_cap[_reverse[a]] += delta; |
---|
[874] | 1529 | _excess[n] -= delta; |
---|
| 1530 | _excess[t] += delta; |
---|
| 1531 | if (_excess[t] > 0 && _excess[t] <= delta) |
---|
[875] | 1532 | _active_nodes.push_back(t); |
---|
[874] | 1533 | } |
---|
| 1534 | |
---|
[875] | 1535 | if (_excess[n] == 0) { |
---|
| 1536 | _next_out[n] = a; |
---|
| 1537 | goto remove_nodes; |
---|
| 1538 | } |
---|
[874] | 1539 | } |
---|
| 1540 | } |
---|
[875] | 1541 | _next_out[n] = a; |
---|
[874] | 1542 | } |
---|
| 1543 | |
---|
| 1544 | // Relabel the node if it is still active (or hyper) |
---|
[875] | 1545 | if (_excess[n] > 0 || hyper[n]) { |
---|
[910] | 1546 | min_red_cost = hyper[n] ? -hyper_cost[n] : |
---|
| 1547 | std::numeric_limits<LargeCost>::max(); |
---|
[875] | 1548 | for (int a = _first_out[n]; a != last_out; ++a) { |
---|
[1046] | 1549 | if (_res_cap[a] > 0) { |
---|
| 1550 | rc = _cost[a] + pi_n - _pi[_target[a]]; |
---|
| 1551 | if (rc < min_red_cost) { |
---|
| 1552 | min_red_cost = rc; |
---|
| 1553 | } |
---|
[875] | 1554 | } |
---|
[874] | 1555 | } |
---|
[875] | 1556 | _pi[n] -= min_red_cost + _epsilon; |
---|
[910] | 1557 | _next_out[n] = _first_out[n]; |
---|
[874] | 1558 | hyper[n] = false; |
---|
[910] | 1559 | ++relabel_cnt; |
---|
[874] | 1560 | } |
---|
[956] | 1561 | |
---|
[874] | 1562 | // Remove nodes that are not active nor hyper |
---|
[875] | 1563 | remove_nodes: |
---|
| 1564 | while ( _active_nodes.size() > 0 && |
---|
| 1565 | _excess[_active_nodes.front()] <= 0 && |
---|
| 1566 | !hyper[_active_nodes.front()] ) { |
---|
| 1567 | _active_nodes.pop_front(); |
---|
[874] | 1568 | } |
---|
[956] | 1569 | |
---|
[910] | 1570 | // Global update heuristic |
---|
[1046] | 1571 | if (relabel_cnt >= next_global_update_limit) { |
---|
[910] | 1572 | globalUpdate(); |
---|
| 1573 | for (int u = 0; u != _res_node_num; ++u) |
---|
| 1574 | hyper[u] = false; |
---|
[1046] | 1575 | next_global_update_limit += global_update_skip; |
---|
[910] | 1576 | } |
---|
[874] | 1577 | } |
---|
| 1578 | } |
---|
| 1579 | } |
---|
| 1580 | |
---|
| 1581 | }; //class CostScaling |
---|
| 1582 | |
---|
| 1583 | ///@} |
---|
| 1584 | |
---|
| 1585 | } //namespace lemon |
---|
| 1586 | |
---|
| 1587 | #endif //LEMON_COST_SCALING_H |
---|