1 | /* -*- C++ -*- |
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2 | * |
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3 | * This file is a part of LEMON, a generic C++ optimization library |
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4 | * |
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5 | * Copyright (C) 2003-2006 |
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6 | * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport |
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7 | * (Egervary Research Group on Combinatorial Optimization, EGRES). |
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8 | * |
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9 | * Permission to use, modify and distribute this software is granted |
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10 | * provided that this copyright notice appears in all copies. For |
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11 | * precise terms see the accompanying LICENSE file. |
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12 | * |
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13 | * This software is provided "AS IS" with no warranty of any kind, |
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14 | * express or implied, and with no claim as to its suitability for any |
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15 | * purpose. |
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16 | * |
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17 | */ |
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18 | |
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19 | /// \ingroup demos |
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20 | /// \file |
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21 | /// \brief A program demonstrating the simulated annealing algorithm class. |
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22 | /// |
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23 | /// This program tries to find a maximal cut in a graph using simulated |
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24 | /// annealing. It starts from a random solution and then in each step it |
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25 | /// chooses a node and moves it to the other side of the cut. |
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26 | /// |
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27 | /// \include simann_maxcut_demo.cc |
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28 | |
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29 | #include <iostream> |
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30 | #include <cstdlib> |
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31 | |
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32 | #include <lemon/simann.h> |
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33 | #include <lemon/list_graph.h> |
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34 | #include <lemon/graph_reader.h> |
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35 | |
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36 | using namespace lemon; |
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37 | |
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38 | typedef ListGraph Graph; |
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39 | typedef Graph::Node Node; |
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40 | typedef Graph::Edge Edge; |
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41 | typedef Graph::NodeIt NodeIt; |
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42 | typedef Graph::EdgeIt EdgeIt; |
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43 | typedef Graph::OutEdgeIt OutEdgeIt; |
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44 | typedef Graph::InEdgeIt InEdgeIt; |
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45 | |
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46 | class Entity : public EntityBase |
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47 | { |
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48 | public: |
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49 | Graph& g; |
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50 | Graph::EdgeMap<int>& w; |
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51 | Graph::NodeMap<bool> a; |
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52 | int sum; |
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53 | Node last_moved; |
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54 | Entity(Graph& _g, Graph::EdgeMap<int>& _w) : g(_g), w(_w), a(_g) {} |
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55 | double mutate() { |
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56 | static const int node_num = countNodes(g); |
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57 | int i = 1 + (int) (node_num * (rand() / (RAND_MAX + 1.0))); |
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58 | NodeIt n(g); |
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59 | int j = 1; |
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60 | while (j < i) { |
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61 | ++n; |
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62 | ++j; |
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63 | } |
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64 | for (OutEdgeIt e(g, n); e != INVALID; ++e) { |
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65 | if (a[n] != a[g.target(e)]) sum -= w[e]; |
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66 | if (a[n] == a[g.target(e)]) sum += w[e]; |
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67 | } |
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68 | for (InEdgeIt e(g, n); e != INVALID; ++e) { |
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69 | if (a[g.source(e)] != a[n]) sum -= w[e]; |
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70 | if (a[g.source(e)] == a[n]) sum += w[e]; |
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71 | } |
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72 | bool b = a[n]; |
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73 | a[n] = !b; |
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74 | last_moved = n; |
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75 | return -sum; |
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76 | } |
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77 | void revert() { |
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78 | for (OutEdgeIt e(g, last_moved); e != INVALID; ++e) { |
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79 | if (a[last_moved] != a[g.target(e)]) sum -= w[e]; |
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80 | if (a[last_moved] == a[g.target(e)]) sum += w[e]; |
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81 | } |
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82 | for (InEdgeIt e(g, last_moved); e != INVALID; ++e) { |
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83 | if (a[g.source(e)] != a[last_moved]) sum -= w[e]; |
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84 | if (a[g.source(e)] == a[last_moved]) sum += w[e]; |
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85 | } |
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86 | bool b = a[last_moved]; |
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87 | a[last_moved] = !b; |
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88 | } |
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89 | Entity* clone() { return new Entity(*this); } |
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90 | void randomize() { |
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91 | for (NodeIt n(g); n != INVALID; ++n) |
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92 | a[n] = false; |
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93 | for (NodeIt n(g); n != INVALID; ++n) |
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94 | if (rand() < 0.5) a[n] = true; |
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95 | sum = 0; |
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96 | for (EdgeIt e(g); e != INVALID; ++e) |
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97 | if (a[g.source(e)] != a[g.target(e)]) |
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98 | sum += w[e]; |
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99 | } |
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100 | }; |
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101 | |
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102 | int main() |
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103 | { |
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104 | Graph g; |
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105 | Graph::EdgeMap<int> w(g); |
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106 | |
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107 | GraphReader<Graph> reader("simann_maxcut_demo.lgf", g); |
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108 | reader.readEdgeMap("weight", w); |
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109 | reader.run(); |
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110 | |
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111 | Entity e(g, w); |
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112 | |
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113 | SimAnn simann; |
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114 | SimpleController ctrl; |
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115 | simann.setController(ctrl); |
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116 | simann.setEntity(e); |
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117 | simann.run(); |
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118 | |
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119 | Entity* be = (Entity *) simann.getBestEntity(); |
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120 | std::cout << be->sum << std::endl; |
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121 | for (NodeIt n(g); n != INVALID; ++n) |
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122 | if (be->a[n]) std::cout << g.id(n) << ": 1" << std::endl; |
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123 | else std::cout << g.id(n) << ": 0" << std::endl; |
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124 | } |
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