[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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| 26 | ///(for small values of \c k) having minimal total cost |
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| 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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| 29 | /// The range of the length (weight) function is nonnegative reals but |
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| 30 | /// the range of capacity function is the set of nonnegative integers. |
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| 31 | /// It is not a polinomial time algorithm for counting the minimum cost |
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| 32 | /// maximal flow, since it counts the minimum cost flow for every value 0..M |
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| 33 | /// where \c M is the value of the maximal flow. |
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| 34 | /// |
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| 35 | ///\author Attila Bernath |
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| 36 | template <typename Graph, typename LengthMap, typename CapacityMap> |
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| 37 | class MinCostFlows { |
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| 38 | |
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| 39 | typedef typename LengthMap::ValueType Length; |
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| 40 | |
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| 41 | //Warning: this should be integer type |
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| 42 | typedef typename CapacityMap::ValueType Capacity; |
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| 43 | |
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| 44 | typedef typename Graph::Node Node; |
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| 45 | typedef typename Graph::NodeIt NodeIt; |
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| 46 | typedef typename Graph::Edge Edge; |
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| 47 | typedef typename Graph::OutEdgeIt OutEdgeIt; |
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| 48 | typedef typename Graph::template EdgeMap<int> EdgeIntMap; |
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| 49 | |
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| 50 | // typedef ConstMap<Edge,int> ConstMap; |
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| 51 | |
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| 52 | typedef ResGraphWrapper<const Graph,int,CapacityMap,EdgeIntMap> ResGraphType; |
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| 53 | typedef typename ResGraphType::Edge ResGraphEdge; |
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| 54 | |
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| 55 | class ModLengthMap { |
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| 56 | //typedef typename ResGraphType::template NodeMap<Length> NodeMap; |
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| 57 | typedef typename Graph::template NodeMap<Length> NodeMap; |
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| 58 | const ResGraphType& G; |
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| 59 | // const EdgeIntMap& rev; |
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| 60 | const LengthMap &ol; |
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| 61 | const NodeMap &pot; |
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| 62 | public : |
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| 63 | typedef typename LengthMap::KeyType KeyType; |
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| 64 | typedef typename LengthMap::ValueType ValueType; |
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| 65 | |
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| 66 | ValueType operator[](typename ResGraphType::Edge e) const { |
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| 67 | if (G.forward(e)) |
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| 68 | return ol[e]-(pot[G.head(e)]-pot[G.tail(e)]); |
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| 69 | else |
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| 70 | return -ol[e]-(pot[G.head(e)]-pot[G.tail(e)]); |
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| 71 | } |
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| 72 | |
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| 73 | ModLengthMap(const ResGraphType& _G, |
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| 74 | const LengthMap &o, const NodeMap &p) : |
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| 75 | G(_G), /*rev(_rev),*/ ol(o), pot(p){}; |
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| 76 | };//ModLengthMap |
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| 77 | |
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| 78 | |
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| 79 | protected: |
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| 80 | |
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| 81 | //Input |
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| 82 | const Graph& G; |
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| 83 | const LengthMap& length; |
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| 84 | const CapacityMap& capacity; |
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| 85 | |
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| 86 | |
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| 87 | //auxiliary variables |
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| 88 | |
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| 89 | //To store the flow |
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| 90 | EdgeIntMap flow; |
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[785] | 91 | //To store the potential (dual variables) |
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[661] | 92 | typedef typename Graph::template NodeMap<Length> PotentialMap; |
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| 93 | PotentialMap potential; |
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[610] | 94 | |
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| 95 | |
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| 96 | Length total_length; |
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| 97 | |
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| 98 | |
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| 99 | public : |
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| 100 | |
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| 101 | |
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| 102 | MinCostFlows(Graph& _G, LengthMap& _length, CapacityMap& _cap) : G(_G), |
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| 103 | length(_length), capacity(_cap), flow(_G), potential(_G){ } |
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| 104 | |
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| 105 | |
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| 106 | ///Runs the algorithm. |
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| 107 | |
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| 108 | ///Runs the algorithm. |
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| 109 | ///Returns k if there are at least k edge-disjoint paths from s to t. |
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| 110 | ///Otherwise it returns the number of found edge-disjoint paths from s to t. |
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| 111 | ///\todo May be it does make sense to be able to start with a nonzero |
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| 112 | /// feasible primal-dual solution pair as well. |
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| 113 | int run(Node s, Node t, int k) { |
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| 114 | |
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| 115 | //Resetting variables from previous runs |
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| 116 | total_length = 0; |
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| 117 | |
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[788] | 118 | for (typename Graph::EdgeIt e(G); e!=INVALID; ++e) flow.set(e, 0); |
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[634] | 119 | |
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| 120 | //Initialize the potential to zero |
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[788] | 121 | for (typename Graph::NodeIt n(G); n!=INVALID; ++n) potential.set(n, 0); |
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[610] | 122 | |
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| 123 | |
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| 124 | //We need a residual graph |
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| 125 | ResGraphType res_graph(G, capacity, flow); |
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| 126 | |
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| 127 | |
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| 128 | ModLengthMap mod_length(res_graph, length, potential); |
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| 129 | |
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| 130 | Dijkstra<ResGraphType, ModLengthMap> dijkstra(res_graph, mod_length); |
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| 131 | |
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| 132 | int i; |
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| 133 | for (i=0; i<k; ++i){ |
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| 134 | dijkstra.run(s); |
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| 135 | if (!dijkstra.reached(t)){ |
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| 136 | //There are no k paths from s to t |
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| 137 | break; |
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| 138 | }; |
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| 139 | |
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[634] | 140 | //We have to change the potential |
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[788] | 141 | for(typename ResGraphType::NodeIt n(res_graph); n!=INVALID; ++n) |
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[633] | 142 | potential[n] += dijkstra.distMap()[n]; |
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[634] | 143 | |
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[610] | 144 | |
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| 145 | //Augmenting on the sortest path |
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| 146 | Node n=t; |
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| 147 | ResGraphEdge e; |
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| 148 | while (n!=s){ |
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| 149 | e = dijkstra.pred(n); |
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| 150 | n = dijkstra.predNode(n); |
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| 151 | res_graph.augment(e,1); |
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| 152 | //Let's update the total length |
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| 153 | if (res_graph.forward(e)) |
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| 154 | total_length += length[e]; |
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| 155 | else |
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| 156 | total_length -= length[e]; |
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| 157 | } |
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| 158 | |
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| 159 | |
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| 160 | } |
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| 161 | |
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| 162 | |
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| 163 | return i; |
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| 164 | } |
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| 165 | |
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| 166 | |
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| 167 | |
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| 168 | |
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| 169 | ///This function gives back the total length of the found paths. |
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| 170 | ///Assumes that \c run() has been run and nothing changed since then. |
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| 171 | Length totalLength(){ |
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| 172 | return total_length; |
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| 173 | } |
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| 174 | |
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| 175 | ///Returns a const reference to the EdgeMap \c flow. \pre \ref run() must |
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| 176 | ///be called before using this function. |
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| 177 | const EdgeIntMap &getFlow() const { return flow;} |
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| 178 | |
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| 179 | ///Returns a const reference to the NodeMap \c potential (the dual solution). |
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| 180 | /// \pre \ref run() must be called before using this function. |
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[661] | 181 | const PotentialMap &getPotential() const { return potential;} |
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[610] | 182 | |
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| 183 | ///This function checks, whether the given solution is optimal |
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| 184 | ///Running after a \c run() should return with true |
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| 185 | ///In this "state of the art" this only check optimality, doesn't bother with feasibility |
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| 186 | /// |
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| 187 | ///\todo Is this OK here? |
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| 188 | bool checkComplementarySlackness(){ |
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| 189 | Length mod_pot; |
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| 190 | Length fl_e; |
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[788] | 191 | for(typename Graph::EdgeIt e(G); e!=INVALID; ++e) { |
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[610] | 192 | //C^{\Pi}_{i,j} |
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| 193 | mod_pot = length[e]-potential[G.head(e)]+potential[G.tail(e)]; |
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| 194 | fl_e = flow[e]; |
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| 195 | // std::cout << fl_e << std::endl; |
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| 196 | if (0<fl_e && fl_e<capacity[e]){ |
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| 197 | if (mod_pot != 0) |
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| 198 | return false; |
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| 199 | } |
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| 200 | else{ |
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| 201 | if (mod_pot > 0 && fl_e != 0) |
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| 202 | return false; |
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| 203 | if (mod_pot < 0 && fl_e != capacity[e]) |
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| 204 | return false; |
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| 205 | } |
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| 206 | } |
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| 207 | return true; |
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| 208 | } |
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| 209 | |
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| 210 | |
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| 211 | }; //class MinCostFlows |
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| 212 | |
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| 213 | ///@} |
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| 214 | |
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| 215 | } //namespace hugo |
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| 216 | |
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[633] | 217 | #endif //HUGO_MINCOSTFLOWS_H |
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