[610] | 1 | // -*- c++ -*- |
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| 2 | #ifndef HUGO_MINCOSTFLOWS_H |
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| 3 | #define HUGO_MINCOSTFLOWS_H |
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| 4 | |
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[758] | 5 | ///\ingroup flowalgs |
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[610] | 6 | ///\file |
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| 7 | ///\brief An algorithm for finding a flow of value \c k (for small values of \c k) having minimal total cost |
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| 8 | |
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[611] | 9 | |
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[610] | 10 | #include <hugo/dijkstra.h> |
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| 11 | #include <hugo/graph_wrapper.h> |
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| 12 | #include <hugo/maps.h> |
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| 13 | #include <vector> |
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| 14 | |
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| 15 | namespace hugo { |
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| 16 | |
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[758] | 17 | /// \addtogroup flowalgs |
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[610] | 18 | /// @{ |
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| 19 | |
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| 20 | ///\brief Implementation of an algorithm for finding a flow of value \c k |
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| 21 | ///(for small values of \c k) having minimal total cost between 2 nodes |
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| 22 | /// |
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| 23 | /// |
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| 24 | /// The class \ref hugo::MinCostFlows "MinCostFlows" implements |
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| 25 | /// an algorithm for finding a flow of value \c k |
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[860] | 26 | /// having minimal total cost |
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[610] | 27 | /// from a given source node to a given target node in an |
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| 28 | /// edge-weighted directed graph having nonnegative integer capacities. |
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[860] | 29 | /// The range of the length (weight or cost) function can be nonnegative reals but |
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| 30 | /// the range of the capacity function has to be the set of nonnegative integers. |
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| 31 | /// This algorithm is intended to use only for for small values of \c k, since /// it is not a polinomial time algorithm for finding the minimum cost |
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| 32 | /// maximal flow (in order to find the minimum cost flow of value \c k it |
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| 33 | /// finds the minimum cost flow of value \c i for every |
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| 34 | /// \c i between 0 and \c k). |
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| 35 | /// |
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| 36 | ///\param Graph The directed graph type the algorithm runs on. |
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| 37 | ///\param LengthMap The type of the length map. |
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| 38 | ///\param CapacityMap The capacity map type. |
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[610] | 39 | /// |
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| 40 | ///\author Attila Bernath |
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| 41 | template <typename Graph, typename LengthMap, typename CapacityMap> |
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| 42 | class MinCostFlows { |
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| 43 | |
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[860] | 44 | |
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| 45 | |
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[610] | 46 | typedef typename LengthMap::ValueType Length; |
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| 47 | |
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| 48 | //Warning: this should be integer type |
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| 49 | typedef typename CapacityMap::ValueType Capacity; |
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| 50 | |
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| 51 | typedef typename Graph::Node Node; |
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| 52 | typedef typename Graph::NodeIt NodeIt; |
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| 53 | typedef typename Graph::Edge Edge; |
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| 54 | typedef typename Graph::OutEdgeIt OutEdgeIt; |
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| 55 | typedef typename Graph::template EdgeMap<int> EdgeIntMap; |
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| 56 | |
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| 57 | |
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| 58 | typedef ResGraphWrapper<const Graph,int,CapacityMap,EdgeIntMap> ResGraphType; |
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| 59 | typedef typename ResGraphType::Edge ResGraphEdge; |
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| 60 | |
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| 61 | class ModLengthMap { |
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| 62 | typedef typename Graph::template NodeMap<Length> NodeMap; |
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| 63 | const ResGraphType& G; |
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| 64 | const LengthMap &ol; |
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| 65 | const NodeMap &pot; |
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| 66 | public : |
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| 67 | typedef typename LengthMap::KeyType KeyType; |
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| 68 | typedef typename LengthMap::ValueType ValueType; |
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| 69 | |
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| 70 | ValueType operator[](typename ResGraphType::Edge e) const { |
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| 71 | if (G.forward(e)) |
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| 72 | return ol[e]-(pot[G.head(e)]-pot[G.tail(e)]); |
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| 73 | else |
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| 74 | return -ol[e]-(pot[G.head(e)]-pot[G.tail(e)]); |
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| 75 | } |
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| 76 | |
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| 77 | ModLengthMap(const ResGraphType& _G, |
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| 78 | const LengthMap &o, const NodeMap &p) : |
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| 79 | G(_G), /*rev(_rev),*/ ol(o), pot(p){}; |
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| 80 | };//ModLengthMap |
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| 81 | |
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| 82 | |
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| 83 | protected: |
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| 84 | |
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| 85 | //Input |
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| 86 | const Graph& G; |
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| 87 | const LengthMap& length; |
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| 88 | const CapacityMap& capacity; |
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| 89 | |
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| 90 | |
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| 91 | //auxiliary variables |
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| 92 | |
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| 93 | //To store the flow |
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| 94 | EdgeIntMap flow; |
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[785] | 95 | //To store the potential (dual variables) |
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[661] | 96 | typedef typename Graph::template NodeMap<Length> PotentialMap; |
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| 97 | PotentialMap potential; |
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[610] | 98 | |
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| 99 | |
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| 100 | Length total_length; |
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| 101 | |
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| 102 | |
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| 103 | public : |
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| 104 | |
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[860] | 105 | /// The constructor of the class. |
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| 106 | |
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| 107 | ///\param _G The directed graph the algorithm runs on. |
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| 108 | ///\param _length The length (weight or cost) of the edges. |
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| 109 | ///\param _cap The capacity of the edges. |
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[610] | 110 | MinCostFlows(Graph& _G, LengthMap& _length, CapacityMap& _cap) : G(_G), |
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| 111 | length(_length), capacity(_cap), flow(_G), potential(_G){ } |
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| 112 | |
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| 113 | |
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| 114 | ///Runs the algorithm. |
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[860] | 115 | |
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[610] | 116 | ///Runs the algorithm. |
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[860] | 117 | ///Returns k if there is a flow of value at least k edge-disjoint |
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| 118 | ///from s to t. |
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| 119 | ///Otherwise it returns the maximum value of a flow from s to t. |
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| 120 | /// |
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| 121 | ///\param s The source node. |
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| 122 | ///\param t The target node. |
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| 123 | ///\param k The value of the flow we are looking for. |
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| 124 | /// |
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[610] | 125 | ///\todo May be it does make sense to be able to start with a nonzero |
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| 126 | /// feasible primal-dual solution pair as well. |
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| 127 | int run(Node s, Node t, int k) { |
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| 128 | |
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| 129 | //Resetting variables from previous runs |
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| 130 | total_length = 0; |
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| 131 | |
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[788] | 132 | for (typename Graph::EdgeIt e(G); e!=INVALID; ++e) flow.set(e, 0); |
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[634] | 133 | |
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| 134 | //Initialize the potential to zero |
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[788] | 135 | for (typename Graph::NodeIt n(G); n!=INVALID; ++n) potential.set(n, 0); |
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[610] | 136 | |
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| 137 | |
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| 138 | //We need a residual graph |
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| 139 | ResGraphType res_graph(G, capacity, flow); |
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| 140 | |
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| 141 | |
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| 142 | ModLengthMap mod_length(res_graph, length, potential); |
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| 143 | |
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| 144 | Dijkstra<ResGraphType, ModLengthMap> dijkstra(res_graph, mod_length); |
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| 145 | |
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| 146 | int i; |
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| 147 | for (i=0; i<k; ++i){ |
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| 148 | dijkstra.run(s); |
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| 149 | if (!dijkstra.reached(t)){ |
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[860] | 150 | //There are no flow of value k from s to t |
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[610] | 151 | break; |
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| 152 | }; |
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| 153 | |
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[634] | 154 | //We have to change the potential |
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[788] | 155 | for(typename ResGraphType::NodeIt n(res_graph); n!=INVALID; ++n) |
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[633] | 156 | potential[n] += dijkstra.distMap()[n]; |
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[634] | 157 | |
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[610] | 158 | |
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| 159 | //Augmenting on the sortest path |
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| 160 | Node n=t; |
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| 161 | ResGraphEdge e; |
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| 162 | while (n!=s){ |
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| 163 | e = dijkstra.pred(n); |
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| 164 | n = dijkstra.predNode(n); |
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| 165 | res_graph.augment(e,1); |
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| 166 | //Let's update the total length |
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| 167 | if (res_graph.forward(e)) |
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| 168 | total_length += length[e]; |
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| 169 | else |
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| 170 | total_length -= length[e]; |
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| 171 | } |
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| 172 | |
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| 173 | |
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| 174 | } |
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| 175 | |
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| 176 | |
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| 177 | return i; |
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| 178 | } |
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| 179 | |
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| 180 | |
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| 181 | |
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[860] | 182 | /// Gives back the total weight of the found flow. |
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[610] | 183 | |
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[860] | 184 | ///This function gives back the total weight of the found flow. |
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[610] | 185 | ///Assumes that \c run() has been run and nothing changed since then. |
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| 186 | Length totalLength(){ |
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| 187 | return total_length; |
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| 188 | } |
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| 189 | |
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[860] | 190 | ///Returns a const reference to the EdgeMap \c flow. |
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| 191 | |
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| 192 | ///Returns a const reference to the EdgeMap \c flow. |
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| 193 | ///\pre \ref run() must |
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[610] | 194 | ///be called before using this function. |
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| 195 | const EdgeIntMap &getFlow() const { return flow;} |
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| 196 | |
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[860] | 197 | ///Returns a const reference to the NodeMap \c potential (the dual solution). |
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| 198 | |
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| 199 | ///Returns a const reference to the NodeMap \c potential (the dual solution). |
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[610] | 200 | /// \pre \ref run() must be called before using this function. |
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[661] | 201 | const PotentialMap &getPotential() const { return potential;} |
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[610] | 202 | |
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[860] | 203 | /// Checking the complementary slackness optimality criteria |
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| 204 | |
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[610] | 205 | ///This function checks, whether the given solution is optimal |
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[860] | 206 | ///If executed after the call of \c run() then it should return with true. |
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| 207 | ///This function only checks optimality, doesn't bother with feasibility. |
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| 208 | ///It is meant for testing purposes. |
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[610] | 209 | /// |
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| 210 | bool checkComplementarySlackness(){ |
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| 211 | Length mod_pot; |
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| 212 | Length fl_e; |
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[788] | 213 | for(typename Graph::EdgeIt e(G); e!=INVALID; ++e) { |
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[610] | 214 | //C^{\Pi}_{i,j} |
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| 215 | mod_pot = length[e]-potential[G.head(e)]+potential[G.tail(e)]; |
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| 216 | fl_e = flow[e]; |
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| 217 | // std::cout << fl_e << std::endl; |
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| 218 | if (0<fl_e && fl_e<capacity[e]){ |
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| 219 | if (mod_pot != 0) |
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| 220 | return false; |
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| 221 | } |
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| 222 | else{ |
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| 223 | if (mod_pot > 0 && fl_e != 0) |
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| 224 | return false; |
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| 225 | if (mod_pot < 0 && fl_e != capacity[e]) |
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| 226 | return false; |
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| 227 | } |
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| 228 | } |
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| 229 | return true; |
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| 230 | } |
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| 231 | |
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| 232 | |
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| 233 | }; //class MinCostFlows |
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| 234 | |
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| 235 | ///@} |
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| 236 | |
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| 237 | } //namespace hugo |
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| 238 | |
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[633] | 239 | #endif //HUGO_MINCOSTFLOWS_H |
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