[956] | 1 | /* -*- mode: C++; indent-tabs-mode: nil; -*- |
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[813] | 2 | * |
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[956] | 3 | * This file is a part of LEMON, a generic C++ optimization library. |
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[813] | 4 | * |
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[956] | 5 | * Copyright (C) 2003-2010 |
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[813] | 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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[942] | 19 | #ifndef LEMON_HARTMANN_ORLIN_MMC_H |
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| 20 | #define LEMON_HARTMANN_ORLIN_MMC_H |
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[813] | 21 | |
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[815] | 22 | /// \ingroup min_mean_cycle |
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[813] | 23 | /// |
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| 24 | /// \file |
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| 25 | /// \brief Hartmann-Orlin's algorithm for finding a minimum mean cycle. |
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| 26 | |
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| 27 | #include <vector> |
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| 28 | #include <limits> |
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| 29 | #include <lemon/core.h> |
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| 30 | #include <lemon/path.h> |
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| 31 | #include <lemon/tolerance.h> |
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| 32 | #include <lemon/connectivity.h> |
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| 33 | |
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| 34 | namespace lemon { |
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| 35 | |
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[942] | 36 | /// \brief Default traits class of HartmannOrlinMmc class. |
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[813] | 37 | /// |
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[942] | 38 | /// Default traits class of HartmannOrlinMmc class. |
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[813] | 39 | /// \tparam GR The type of the digraph. |
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[942] | 40 | /// \tparam CM The type of the cost map. |
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[959] | 41 | /// It must conform to the \ref concepts::ReadMap "ReadMap" concept. |
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[813] | 42 | #ifdef DOXYGEN |
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[942] | 43 | template <typename GR, typename CM> |
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[813] | 44 | #else |
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[942] | 45 | template <typename GR, typename CM, |
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| 46 | bool integer = std::numeric_limits<typename CM::Value>::is_integer> |
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[813] | 47 | #endif |
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[942] | 48 | struct HartmannOrlinMmcDefaultTraits |
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[813] | 49 | { |
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| 50 | /// The type of the digraph |
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| 51 | typedef GR Digraph; |
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[942] | 52 | /// The type of the cost map |
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| 53 | typedef CM CostMap; |
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| 54 | /// The type of the arc costs |
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| 55 | typedef typename CostMap::Value Cost; |
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[813] | 56 | |
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[942] | 57 | /// \brief The large cost type used for internal computations |
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[813] | 58 | /// |
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[942] | 59 | /// The large cost type used for internal computations. |
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| 60 | /// It is \c long \c long if the \c Cost type is integer, |
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[813] | 61 | /// otherwise it is \c double. |
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[942] | 62 | /// \c Cost must be convertible to \c LargeCost. |
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| 63 | typedef double LargeCost; |
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[813] | 64 | |
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| 65 | /// The tolerance type used for internal computations |
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[942] | 66 | typedef lemon::Tolerance<LargeCost> Tolerance; |
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[813] | 67 | |
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| 68 | /// \brief The path type of the found cycles |
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| 69 | /// |
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| 70 | /// The path type of the found cycles. |
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| 71 | /// It must conform to the \ref lemon::concepts::Path "Path" concept |
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[819] | 72 | /// and it must have an \c addFront() function. |
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[813] | 73 | typedef lemon::Path<Digraph> Path; |
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| 74 | }; |
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| 75 | |
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[942] | 76 | // Default traits class for integer cost types |
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| 77 | template <typename GR, typename CM> |
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| 78 | struct HartmannOrlinMmcDefaultTraits<GR, CM, true> |
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[813] | 79 | { |
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| 80 | typedef GR Digraph; |
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[942] | 81 | typedef CM CostMap; |
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| 82 | typedef typename CostMap::Value Cost; |
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[813] | 83 | #ifdef LEMON_HAVE_LONG_LONG |
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[942] | 84 | typedef long long LargeCost; |
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[813] | 85 | #else |
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[942] | 86 | typedef long LargeCost; |
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[813] | 87 | #endif |
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[942] | 88 | typedef lemon::Tolerance<LargeCost> Tolerance; |
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[813] | 89 | typedef lemon::Path<Digraph> Path; |
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| 90 | }; |
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| 91 | |
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| 92 | |
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[815] | 93 | /// \addtogroup min_mean_cycle |
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[813] | 94 | /// @{ |
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| 95 | |
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| 96 | /// \brief Implementation of the Hartmann-Orlin algorithm for finding |
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| 97 | /// a minimum mean cycle. |
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| 98 | /// |
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| 99 | /// This class implements the Hartmann-Orlin algorithm for finding |
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[942] | 100 | /// a directed cycle of minimum mean cost in a digraph |
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[1164] | 101 | /// \ref hartmann93finding, \ref dasdan98minmeancycle. |
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[959] | 102 | /// It is an improved version of \ref KarpMmc "Karp"'s original algorithm, |
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[813] | 103 | /// it applies an efficient early termination scheme. |
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[815] | 104 | /// It runs in time O(ne) and uses space O(n<sup>2</sup>+e). |
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[813] | 105 | /// |
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| 106 | /// \tparam GR The type of the digraph the algorithm runs on. |
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[942] | 107 | /// \tparam CM The type of the cost map. The default |
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[813] | 108 | /// map type is \ref concepts::Digraph::ArcMap "GR::ArcMap<int>". |
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[891] | 109 | /// \tparam TR The traits class that defines various types used by the |
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[942] | 110 | /// algorithm. By default, it is \ref HartmannOrlinMmcDefaultTraits |
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| 111 | /// "HartmannOrlinMmcDefaultTraits<GR, CM>". |
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[891] | 112 | /// In most cases, this parameter should not be set directly, |
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| 113 | /// consider to use the named template parameters instead. |
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[813] | 114 | #ifdef DOXYGEN |
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[942] | 115 | template <typename GR, typename CM, typename TR> |
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[813] | 116 | #else |
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| 117 | template < typename GR, |
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[942] | 118 | typename CM = typename GR::template ArcMap<int>, |
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| 119 | typename TR = HartmannOrlinMmcDefaultTraits<GR, CM> > |
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[813] | 120 | #endif |
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[942] | 121 | class HartmannOrlinMmc |
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[813] | 122 | { |
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| 123 | public: |
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| 124 | |
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| 125 | /// The type of the digraph |
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| 126 | typedef typename TR::Digraph Digraph; |
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[942] | 127 | /// The type of the cost map |
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| 128 | typedef typename TR::CostMap CostMap; |
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| 129 | /// The type of the arc costs |
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| 130 | typedef typename TR::Cost Cost; |
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[813] | 131 | |
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[942] | 132 | /// \brief The large cost type |
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[813] | 133 | /// |
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[942] | 134 | /// The large cost type used for internal computations. |
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| 135 | /// By default, it is \c long \c long if the \c Cost type is integer, |
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[813] | 136 | /// otherwise it is \c double. |
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[942] | 137 | typedef typename TR::LargeCost LargeCost; |
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[813] | 138 | |
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| 139 | /// The tolerance type |
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| 140 | typedef typename TR::Tolerance Tolerance; |
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| 141 | |
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| 142 | /// \brief The path type of the found cycles |
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| 143 | /// |
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| 144 | /// The path type of the found cycles. |
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[942] | 145 | /// Using the \ref HartmannOrlinMmcDefaultTraits "default traits class", |
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[813] | 146 | /// it is \ref lemon::Path "Path<Digraph>". |
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| 147 | typedef typename TR::Path Path; |
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| 148 | |
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[942] | 149 | /// The \ref HartmannOrlinMmcDefaultTraits "traits class" of the algorithm |
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[813] | 150 | typedef TR Traits; |
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| 151 | |
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| 152 | private: |
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| 153 | |
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| 154 | TEMPLATE_DIGRAPH_TYPEDEFS(Digraph); |
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| 155 | |
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| 156 | // Data sturcture for path data |
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| 157 | struct PathData |
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| 158 | { |
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[942] | 159 | LargeCost dist; |
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[813] | 160 | Arc pred; |
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[942] | 161 | PathData(LargeCost d, Arc p = INVALID) : |
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[814] | 162 | dist(d), pred(p) {} |
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[813] | 163 | }; |
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| 164 | |
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| 165 | typedef typename Digraph::template NodeMap<std::vector<PathData> > |
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| 166 | PathDataNodeMap; |
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| 167 | |
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| 168 | private: |
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| 169 | |
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| 170 | // The digraph the algorithm runs on |
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| 171 | const Digraph &_gr; |
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[942] | 172 | // The cost of the arcs |
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| 173 | const CostMap &_cost; |
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[813] | 174 | |
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| 175 | // Data for storing the strongly connected components |
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| 176 | int _comp_num; |
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| 177 | typename Digraph::template NodeMap<int> _comp; |
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| 178 | std::vector<std::vector<Node> > _comp_nodes; |
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| 179 | std::vector<Node>* _nodes; |
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| 180 | typename Digraph::template NodeMap<std::vector<Arc> > _out_arcs; |
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| 181 | |
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| 182 | // Data for the found cycles |
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| 183 | bool _curr_found, _best_found; |
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[942] | 184 | LargeCost _curr_cost, _best_cost; |
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[813] | 185 | int _curr_size, _best_size; |
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| 186 | Node _curr_node, _best_node; |
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| 187 | int _curr_level, _best_level; |
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| 188 | |
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| 189 | Path *_cycle_path; |
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| 190 | bool _local_path; |
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| 191 | |
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| 192 | // Node map for storing path data |
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| 193 | PathDataNodeMap _data; |
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| 194 | // The processed nodes in the last round |
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| 195 | std::vector<Node> _process; |
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| 196 | |
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| 197 | Tolerance _tolerance; |
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| 198 | |
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[814] | 199 | // Infinite constant |
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[942] | 200 | const LargeCost INF; |
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[814] | 201 | |
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[813] | 202 | public: |
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| 203 | |
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| 204 | /// \name Named Template Parameters |
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| 205 | /// @{ |
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| 206 | |
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| 207 | template <typename T> |
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[942] | 208 | struct SetLargeCostTraits : public Traits { |
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| 209 | typedef T LargeCost; |
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[813] | 210 | typedef lemon::Tolerance<T> Tolerance; |
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| 211 | }; |
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| 212 | |
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| 213 | /// \brief \ref named-templ-param "Named parameter" for setting |
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[942] | 214 | /// \c LargeCost type. |
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[813] | 215 | /// |
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[942] | 216 | /// \ref named-templ-param "Named parameter" for setting \c LargeCost |
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[813] | 217 | /// type. It is used for internal computations in the algorithm. |
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| 218 | template <typename T> |
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[942] | 219 | struct SetLargeCost |
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| 220 | : public HartmannOrlinMmc<GR, CM, SetLargeCostTraits<T> > { |
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| 221 | typedef HartmannOrlinMmc<GR, CM, SetLargeCostTraits<T> > Create; |
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[813] | 222 | }; |
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| 223 | |
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| 224 | template <typename T> |
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| 225 | struct SetPathTraits : public Traits { |
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| 226 | typedef T Path; |
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| 227 | }; |
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| 228 | |
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| 229 | /// \brief \ref named-templ-param "Named parameter" for setting |
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| 230 | /// \c %Path type. |
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| 231 | /// |
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| 232 | /// \ref named-templ-param "Named parameter" for setting the \c %Path |
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| 233 | /// type of the found cycles. |
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| 234 | /// It must conform to the \ref lemon::concepts::Path "Path" concept |
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| 235 | /// and it must have an \c addFront() function. |
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| 236 | template <typename T> |
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| 237 | struct SetPath |
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[942] | 238 | : public HartmannOrlinMmc<GR, CM, SetPathTraits<T> > { |
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| 239 | typedef HartmannOrlinMmc<GR, CM, SetPathTraits<T> > Create; |
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[813] | 240 | }; |
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| 241 | |
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| 242 | /// @} |
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| 243 | |
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[941] | 244 | protected: |
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| 245 | |
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[942] | 246 | HartmannOrlinMmc() {} |
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[941] | 247 | |
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[813] | 248 | public: |
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| 249 | |
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| 250 | /// \brief Constructor. |
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| 251 | /// |
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| 252 | /// The constructor of the class. |
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| 253 | /// |
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| 254 | /// \param digraph The digraph the algorithm runs on. |
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[942] | 255 | /// \param cost The costs of the arcs. |
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| 256 | HartmannOrlinMmc( const Digraph &digraph, |
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| 257 | const CostMap &cost ) : |
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| 258 | _gr(digraph), _cost(cost), _comp(digraph), _out_arcs(digraph), |
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| 259 | _best_found(false), _best_cost(0), _best_size(1), |
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[814] | 260 | _cycle_path(NULL), _local_path(false), _data(digraph), |
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[942] | 261 | INF(std::numeric_limits<LargeCost>::has_infinity ? |
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| 262 | std::numeric_limits<LargeCost>::infinity() : |
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| 263 | std::numeric_limits<LargeCost>::max()) |
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[813] | 264 | {} |
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| 265 | |
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| 266 | /// Destructor. |
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[942] | 267 | ~HartmannOrlinMmc() { |
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[813] | 268 | if (_local_path) delete _cycle_path; |
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| 269 | } |
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| 270 | |
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| 271 | /// \brief Set the path structure for storing the found cycle. |
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| 272 | /// |
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| 273 | /// This function sets an external path structure for storing the |
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| 274 | /// found cycle. |
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| 275 | /// |
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| 276 | /// If you don't call this function before calling \ref run() or |
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[942] | 277 | /// \ref findCycleMean(), it will allocate a local \ref Path "path" |
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[813] | 278 | /// structure. The destuctor deallocates this automatically |
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| 279 | /// allocated object, of course. |
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| 280 | /// |
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| 281 | /// \note The algorithm calls only the \ref lemon::Path::addFront() |
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| 282 | /// "addFront()" function of the given path structure. |
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| 283 | /// |
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| 284 | /// \return <tt>(*this)</tt> |
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[942] | 285 | HartmannOrlinMmc& cycle(Path &path) { |
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[813] | 286 | if (_local_path) { |
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| 287 | delete _cycle_path; |
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| 288 | _local_path = false; |
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| 289 | } |
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| 290 | _cycle_path = &path; |
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| 291 | return *this; |
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| 292 | } |
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| 293 | |
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[816] | 294 | /// \brief Set the tolerance used by the algorithm. |
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| 295 | /// |
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| 296 | /// This function sets the tolerance object used by the algorithm. |
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| 297 | /// |
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| 298 | /// \return <tt>(*this)</tt> |
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[942] | 299 | HartmannOrlinMmc& tolerance(const Tolerance& tolerance) { |
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[816] | 300 | _tolerance = tolerance; |
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| 301 | return *this; |
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| 302 | } |
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| 303 | |
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| 304 | /// \brief Return a const reference to the tolerance. |
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| 305 | /// |
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| 306 | /// This function returns a const reference to the tolerance object |
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| 307 | /// used by the algorithm. |
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| 308 | const Tolerance& tolerance() const { |
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| 309 | return _tolerance; |
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| 310 | } |
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| 311 | |
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[813] | 312 | /// \name Execution control |
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| 313 | /// The simplest way to execute the algorithm is to call the \ref run() |
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| 314 | /// function.\n |
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[942] | 315 | /// If you only need the minimum mean cost, you may call |
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| 316 | /// \ref findCycleMean(). |
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[813] | 317 | |
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| 318 | /// @{ |
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| 319 | |
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| 320 | /// \brief Run the algorithm. |
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| 321 | /// |
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| 322 | /// This function runs the algorithm. |
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| 323 | /// It can be called more than once (e.g. if the underlying digraph |
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[942] | 324 | /// and/or the arc costs have been modified). |
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[813] | 325 | /// |
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| 326 | /// \return \c true if a directed cycle exists in the digraph. |
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| 327 | /// |
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| 328 | /// \note <tt>mmc.run()</tt> is just a shortcut of the following code. |
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| 329 | /// \code |
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[942] | 330 | /// return mmc.findCycleMean() && mmc.findCycle(); |
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[813] | 331 | /// \endcode |
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| 332 | bool run() { |
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[942] | 333 | return findCycleMean() && findCycle(); |
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[813] | 334 | } |
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| 335 | |
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| 336 | /// \brief Find the minimum cycle mean. |
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| 337 | /// |
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[942] | 338 | /// This function finds the minimum mean cost of the directed |
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[813] | 339 | /// cycles in the digraph. |
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| 340 | /// |
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| 341 | /// \return \c true if a directed cycle exists in the digraph. |
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[942] | 342 | bool findCycleMean() { |
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[813] | 343 | // Initialization and find strongly connected components |
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| 344 | init(); |
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| 345 | findComponents(); |
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[956] | 346 | |
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[813] | 347 | // Find the minimum cycle mean in the components |
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| 348 | for (int comp = 0; comp < _comp_num; ++comp) { |
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| 349 | if (!initComponent(comp)) continue; |
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| 350 | processRounds(); |
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[956] | 351 | |
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[813] | 352 | // Update the best cycle (global minimum mean cycle) |
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[956] | 353 | if ( _curr_found && (!_best_found || |
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[942] | 354 | _curr_cost * _best_size < _best_cost * _curr_size) ) { |
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[813] | 355 | _best_found = true; |
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[942] | 356 | _best_cost = _curr_cost; |
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[813] | 357 | _best_size = _curr_size; |
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| 358 | _best_node = _curr_node; |
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| 359 | _best_level = _curr_level; |
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| 360 | } |
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| 361 | } |
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| 362 | return _best_found; |
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| 363 | } |
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| 364 | |
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| 365 | /// \brief Find a minimum mean directed cycle. |
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| 366 | /// |
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[942] | 367 | /// This function finds a directed cycle of minimum mean cost |
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| 368 | /// in the digraph using the data computed by findCycleMean(). |
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[813] | 369 | /// |
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| 370 | /// \return \c true if a directed cycle exists in the digraph. |
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| 371 | /// |
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[942] | 372 | /// \pre \ref findCycleMean() must be called before using this function. |
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[813] | 373 | bool findCycle() { |
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| 374 | if (!_best_found) return false; |
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| 375 | IntNodeMap reached(_gr, -1); |
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| 376 | int r = _best_level + 1; |
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| 377 | Node u = _best_node; |
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| 378 | while (reached[u] < 0) { |
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| 379 | reached[u] = --r; |
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| 380 | u = _gr.source(_data[u][r].pred); |
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| 381 | } |
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| 382 | r = reached[u]; |
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| 383 | Arc e = _data[u][r].pred; |
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| 384 | _cycle_path->addFront(e); |
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[942] | 385 | _best_cost = _cost[e]; |
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[813] | 386 | _best_size = 1; |
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| 387 | Node v; |
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| 388 | while ((v = _gr.source(e)) != u) { |
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| 389 | e = _data[v][--r].pred; |
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| 390 | _cycle_path->addFront(e); |
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[942] | 391 | _best_cost += _cost[e]; |
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[813] | 392 | ++_best_size; |
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| 393 | } |
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| 394 | return true; |
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| 395 | } |
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| 396 | |
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| 397 | /// @} |
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| 398 | |
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| 399 | /// \name Query Functions |
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| 400 | /// The results of the algorithm can be obtained using these |
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| 401 | /// functions.\n |
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| 402 | /// The algorithm should be executed before using them. |
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| 403 | |
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| 404 | /// @{ |
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| 405 | |
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[942] | 406 | /// \brief Return the total cost of the found cycle. |
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[813] | 407 | /// |
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[942] | 408 | /// This function returns the total cost of the found cycle. |
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[813] | 409 | /// |
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[942] | 410 | /// \pre \ref run() or \ref findCycleMean() must be called before |
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[813] | 411 | /// using this function. |
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[942] | 412 | Cost cycleCost() const { |
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| 413 | return static_cast<Cost>(_best_cost); |
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[813] | 414 | } |
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| 415 | |
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| 416 | /// \brief Return the number of arcs on the found cycle. |
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| 417 | /// |
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| 418 | /// This function returns the number of arcs on the found cycle. |
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| 419 | /// |
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[942] | 420 | /// \pre \ref run() or \ref findCycleMean() must be called before |
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[813] | 421 | /// using this function. |
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[942] | 422 | int cycleSize() const { |
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[813] | 423 | return _best_size; |
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| 424 | } |
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| 425 | |
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[942] | 426 | /// \brief Return the mean cost of the found cycle. |
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[813] | 427 | /// |
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[942] | 428 | /// This function returns the mean cost of the found cycle. |
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[813] | 429 | /// |
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| 430 | /// \note <tt>alg.cycleMean()</tt> is just a shortcut of the |
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| 431 | /// following code. |
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| 432 | /// \code |
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[942] | 433 | /// return static_cast<double>(alg.cycleCost()) / alg.cycleSize(); |
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[813] | 434 | /// \endcode |
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| 435 | /// |
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[942] | 436 | /// \pre \ref run() or \ref findCycleMean() must be called before |
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[813] | 437 | /// using this function. |
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| 438 | double cycleMean() const { |
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[942] | 439 | return static_cast<double>(_best_cost) / _best_size; |
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[813] | 440 | } |
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| 441 | |
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| 442 | /// \brief Return the found cycle. |
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| 443 | /// |
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| 444 | /// This function returns a const reference to the path structure |
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| 445 | /// storing the found cycle. |
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| 446 | /// |
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| 447 | /// \pre \ref run() or \ref findCycle() must be called before using |
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| 448 | /// this function. |
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| 449 | const Path& cycle() const { |
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| 450 | return *_cycle_path; |
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| 451 | } |
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| 452 | |
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| 453 | ///@} |
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| 454 | |
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| 455 | private: |
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| 456 | |
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| 457 | // Initialization |
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| 458 | void init() { |
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| 459 | if (!_cycle_path) { |
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| 460 | _local_path = true; |
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| 461 | _cycle_path = new Path; |
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| 462 | } |
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| 463 | _cycle_path->clear(); |
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| 464 | _best_found = false; |
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[942] | 465 | _best_cost = 0; |
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[813] | 466 | _best_size = 1; |
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| 467 | _cycle_path->clear(); |
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| 468 | for (NodeIt u(_gr); u != INVALID; ++u) |
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| 469 | _data[u].clear(); |
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| 470 | } |
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| 471 | |
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| 472 | // Find strongly connected components and initialize _comp_nodes |
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| 473 | // and _out_arcs |
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| 474 | void findComponents() { |
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| 475 | _comp_num = stronglyConnectedComponents(_gr, _comp); |
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| 476 | _comp_nodes.resize(_comp_num); |
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| 477 | if (_comp_num == 1) { |
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| 478 | _comp_nodes[0].clear(); |
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| 479 | for (NodeIt n(_gr); n != INVALID; ++n) { |
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| 480 | _comp_nodes[0].push_back(n); |
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| 481 | _out_arcs[n].clear(); |
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| 482 | for (OutArcIt a(_gr, n); a != INVALID; ++a) { |
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| 483 | _out_arcs[n].push_back(a); |
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| 484 | } |
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| 485 | } |
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| 486 | } else { |
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| 487 | for (int i = 0; i < _comp_num; ++i) |
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| 488 | _comp_nodes[i].clear(); |
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| 489 | for (NodeIt n(_gr); n != INVALID; ++n) { |
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| 490 | int k = _comp[n]; |
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| 491 | _comp_nodes[k].push_back(n); |
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| 492 | _out_arcs[n].clear(); |
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| 493 | for (OutArcIt a(_gr, n); a != INVALID; ++a) { |
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| 494 | if (_comp[_gr.target(a)] == k) _out_arcs[n].push_back(a); |
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| 495 | } |
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| 496 | } |
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| 497 | } |
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| 498 | } |
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| 499 | |
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| 500 | // Initialize path data for the current component |
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| 501 | bool initComponent(int comp) { |
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| 502 | _nodes = &(_comp_nodes[comp]); |
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| 503 | int n = _nodes->size(); |
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| 504 | if (n < 1 || (n == 1 && _out_arcs[(*_nodes)[0]].size() == 0)) { |
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| 505 | return false; |
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[956] | 506 | } |
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[813] | 507 | for (int i = 0; i < n; ++i) { |
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[814] | 508 | _data[(*_nodes)[i]].resize(n + 1, PathData(INF)); |
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[813] | 509 | } |
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| 510 | return true; |
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| 511 | } |
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| 512 | |
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| 513 | // Process all rounds of computing path data for the current component. |
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[942] | 514 | // _data[v][k] is the cost of a shortest directed walk from the root |
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[813] | 515 | // node to node v containing exactly k arcs. |
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| 516 | void processRounds() { |
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| 517 | Node start = (*_nodes)[0]; |
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[814] | 518 | _data[start][0] = PathData(0); |
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[813] | 519 | _process.clear(); |
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| 520 | _process.push_back(start); |
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| 521 | |
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| 522 | int k, n = _nodes->size(); |
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| 523 | int next_check = 4; |
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| 524 | bool terminate = false; |
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| 525 | for (k = 1; k <= n && int(_process.size()) < n && !terminate; ++k) { |
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| 526 | processNextBuildRound(k); |
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| 527 | if (k == next_check || k == n) { |
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| 528 | terminate = checkTermination(k); |
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| 529 | next_check = next_check * 3 / 2; |
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| 530 | } |
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| 531 | } |
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| 532 | for ( ; k <= n && !terminate; ++k) { |
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| 533 | processNextFullRound(k); |
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| 534 | if (k == next_check || k == n) { |
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| 535 | terminate = checkTermination(k); |
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| 536 | next_check = next_check * 3 / 2; |
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| 537 | } |
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| 538 | } |
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| 539 | } |
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| 540 | |
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| 541 | // Process one round and rebuild _process |
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| 542 | void processNextBuildRound(int k) { |
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| 543 | std::vector<Node> next; |
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| 544 | Node u, v; |
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| 545 | Arc e; |
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[942] | 546 | LargeCost d; |
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[813] | 547 | for (int i = 0; i < int(_process.size()); ++i) { |
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| 548 | u = _process[i]; |
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| 549 | for (int j = 0; j < int(_out_arcs[u].size()); ++j) { |
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| 550 | e = _out_arcs[u][j]; |
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| 551 | v = _gr.target(e); |
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[942] | 552 | d = _data[u][k-1].dist + _cost[e]; |
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[814] | 553 | if (_tolerance.less(d, _data[v][k].dist)) { |
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| 554 | if (_data[v][k].dist == INF) next.push_back(v); |
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| 555 | _data[v][k] = PathData(d, e); |
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[813] | 556 | } |
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| 557 | } |
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| 558 | } |
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| 559 | _process.swap(next); |
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| 560 | } |
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| 561 | |
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| 562 | // Process one round using _nodes instead of _process |
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| 563 | void processNextFullRound(int k) { |
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| 564 | Node u, v; |
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| 565 | Arc e; |
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[942] | 566 | LargeCost d; |
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[813] | 567 | for (int i = 0; i < int(_nodes->size()); ++i) { |
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| 568 | u = (*_nodes)[i]; |
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| 569 | for (int j = 0; j < int(_out_arcs[u].size()); ++j) { |
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| 570 | e = _out_arcs[u][j]; |
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| 571 | v = _gr.target(e); |
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[942] | 572 | d = _data[u][k-1].dist + _cost[e]; |
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[814] | 573 | if (_tolerance.less(d, _data[v][k].dist)) { |
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| 574 | _data[v][k] = PathData(d, e); |
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[813] | 575 | } |
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| 576 | } |
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| 577 | } |
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| 578 | } |
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[956] | 579 | |
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[813] | 580 | // Check early termination |
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| 581 | bool checkTermination(int k) { |
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| 582 | typedef std::pair<int, int> Pair; |
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| 583 | typename GR::template NodeMap<Pair> level(_gr, Pair(-1, 0)); |
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[942] | 584 | typename GR::template NodeMap<LargeCost> pi(_gr); |
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[813] | 585 | int n = _nodes->size(); |
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[942] | 586 | LargeCost cost; |
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[813] | 587 | int size; |
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| 588 | Node u; |
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[956] | 589 | |
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[813] | 590 | // Search for cycles that are already found |
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| 591 | _curr_found = false; |
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| 592 | for (int i = 0; i < n; ++i) { |
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| 593 | u = (*_nodes)[i]; |
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[814] | 594 | if (_data[u][k].dist == INF) continue; |
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[813] | 595 | for (int j = k; j >= 0; --j) { |
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| 596 | if (level[u].first == i && level[u].second > 0) { |
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| 597 | // A cycle is found |
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[942] | 598 | cost = _data[u][level[u].second].dist - _data[u][j].dist; |
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[813] | 599 | size = level[u].second - j; |
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[942] | 600 | if (!_curr_found || cost * _curr_size < _curr_cost * size) { |
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| 601 | _curr_cost = cost; |
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[813] | 602 | _curr_size = size; |
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| 603 | _curr_node = u; |
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| 604 | _curr_level = level[u].second; |
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| 605 | _curr_found = true; |
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| 606 | } |
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| 607 | } |
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| 608 | level[u] = Pair(i, j); |
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[859] | 609 | if (j != 0) { |
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[956] | 610 | u = _gr.source(_data[u][j].pred); |
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| 611 | } |
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[813] | 612 | } |
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| 613 | } |
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| 614 | |
---|
| 615 | // If at least one cycle is found, check the optimality condition |
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[942] | 616 | LargeCost d; |
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[813] | 617 | if (_curr_found && k < n) { |
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| 618 | // Find node potentials |
---|
| 619 | for (int i = 0; i < n; ++i) { |
---|
| 620 | u = (*_nodes)[i]; |
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[814] | 621 | pi[u] = INF; |
---|
[813] | 622 | for (int j = 0; j <= k; ++j) { |
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[814] | 623 | if (_data[u][j].dist < INF) { |
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[942] | 624 | d = _data[u][j].dist * _curr_size - j * _curr_cost; |
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[814] | 625 | if (_tolerance.less(d, pi[u])) pi[u] = d; |
---|
[813] | 626 | } |
---|
| 627 | } |
---|
| 628 | } |
---|
| 629 | |
---|
| 630 | // Check the optimality condition for all arcs |
---|
| 631 | bool done = true; |
---|
| 632 | for (ArcIt a(_gr); a != INVALID; ++a) { |
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[942] | 633 | if (_tolerance.less(_cost[a] * _curr_size - _curr_cost, |
---|
[813] | 634 | pi[_gr.target(a)] - pi[_gr.source(a)]) ) { |
---|
| 635 | done = false; |
---|
| 636 | break; |
---|
| 637 | } |
---|
| 638 | } |
---|
| 639 | return done; |
---|
| 640 | } |
---|
| 641 | return (k == n); |
---|
| 642 | } |
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| 643 | |
---|
[942] | 644 | }; //class HartmannOrlinMmc |
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[813] | 645 | |
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| 646 | ///@} |
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| 647 | |
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| 648 | } //namespace lemon |
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| 649 | |
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[942] | 650 | #endif //LEMON_HARTMANN_ORLIN_MMC_H |
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