| 1 | // -*- c++ -*- | 
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| 2 | #ifndef HUGO_MINCOSTFLOW_H | 
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| 3 | #define HUGO_MINCOSTFLOW_H | 
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| 4 |  | 
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| 5 | ///\ingroup galgs | 
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| 6 | ///\file | 
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| 7 | ///\brief An algorithm for finding the minimum cost flow of given value in an uncapacitated network | 
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| 8 |  | 
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| 9 | #include <hugo/dijkstra.h> | 
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| 10 | #include <hugo/graph_wrapper.h> | 
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| 11 | #include <hugo/maps.h> | 
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| 12 | #include <vector> | 
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| 13 | #include <list> | 
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| 14 | #include <values.h> | 
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| 15 | #include <hugo/for_each_macros.h> | 
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| 16 | #include <hugo/unionfind.h> | 
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| 17 | #include <hugo/bin_heap.h> | 
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| 18 | #include <bfs_dfs.h> | 
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| 19 |  | 
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| 20 | namespace hugo { | 
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| 21 |  | 
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| 22 | /// \addtogroup galgs | 
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| 23 | /// @{ | 
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| 24 |  | 
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| 25 |   ///\brief Implementation of an algorithm for solving the minimum cost general | 
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| 26 |   /// flow problem in an uncapacitated network | 
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| 27 |   ///  | 
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| 28 |   /// | 
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| 29 |   /// The class \ref hugo::MinCostFlow "MinCostFlow" implements | 
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| 30 |   /// an algorithm for solving the following general minimum cost flow problem> | 
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| 31 |   ///  | 
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| 32 |   /// | 
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| 33 |   /// | 
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| 34 |   /// \warning It is assumed here that the problem has a feasible solution | 
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| 35 |   /// | 
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| 36 |   /// The range of the cost (weight) function is nonnegative reals but  | 
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| 37 |   /// the range of capacity function is the set of nonnegative integers.  | 
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| 38 |   /// It is not a polinomial time algorithm for counting the minimum cost | 
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| 39 |   /// maximal flow, since it counts the minimum cost flow for every value 0..M | 
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| 40 |   /// where \c M is the value of the maximal flow. | 
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| 41 |   /// | 
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| 42 |   ///\author Attila Bernath | 
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| 43 |   template <typename Graph, typename CostMap, typename SupplyDemandMap> | 
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| 44 |   class MinCostFlow { | 
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| 45 |  | 
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| 46 |     typedef typename CostMap::ValueType Cost; | 
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| 47 |  | 
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| 48 |  | 
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| 49 |     typedef typename SupplyDemandMap::ValueType SupplyDemand; | 
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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<SupplyDemand> FlowMap; | 
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| 56 |     typedef ConstMap<Edge,SupplyDemand> ConstEdgeMap; | 
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| 57 |  | 
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| 58 |     //    typedef ConstMap<Edge,int> ConstMap; | 
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| 59 |  | 
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| 60 |     typedef ResGraphWrapper<const Graph,int,ConstEdgeMap,FlowMap> ResGraph; | 
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| 61 |     typedef typename ResGraph::Edge ResGraphEdge; | 
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| 62 |  | 
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| 63 |     class ModCostMap {    | 
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| 64 |       //typedef typename ResGraph::template NodeMap<Cost> NodeMap; | 
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| 65 |       typedef typename Graph::template NodeMap<Cost> NodeMap; | 
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| 66 |       const ResGraph& res_graph; | 
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| 67 |       //      const EdgeIntMap& rev; | 
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| 68 |       const CostMap &ol; | 
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| 69 |       const NodeMap &pot; | 
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| 70 |     public : | 
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| 71 |       typedef typename CostMap::KeyType KeyType; | 
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| 72 |       typedef typename CostMap::ValueType ValueType; | 
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| 73 |          | 
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| 74 |       ValueType operator[](typename ResGraph::Edge e) const {      | 
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| 75 |         if (res_graph.forward(e)) | 
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| 76 |           return  ol[e]-(pot[res_graph.head(e)]-pot[res_graph.tail(e)]);    | 
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| 77 |         else | 
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| 78 |           return -ol[e]-(pot[res_graph.head(e)]-pot[res_graph.tail(e)]);    | 
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| 79 |       }      | 
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| 80 |          | 
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| 81 |       ModCostMap(const ResGraph& _res_graph, | 
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| 82 |                    const CostMap &o,  const NodeMap &p) :  | 
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| 83 |         res_graph(_res_graph), /*rev(_rev),*/ ol(o), pot(p){};  | 
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| 84 |     };//ModCostMap | 
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| 85 |  | 
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| 86 |  | 
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| 87 |   protected: | 
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| 88 |      | 
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| 89 |     //Input | 
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| 90 |     const Graph& graph; | 
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| 91 |     const CostMap& cost; | 
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| 92 |     const SupplyDemandMap& supply_demand;//supply or demand of nodes | 
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| 93 |  | 
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| 94 |  | 
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| 95 |     //auxiliary variables | 
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| 96 |  | 
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| 97 |     //To store the flow | 
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| 98 |     FlowMap flow;  | 
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| 99 |     //To store the potential (dual variables) | 
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| 100 |     typedef typename Graph::template NodeMap<Cost> PotentialMap; | 
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| 101 |     PotentialMap potential; | 
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| 102 |      | 
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| 103 |  | 
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| 104 |     Cost total_cost; | 
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| 105 |  | 
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| 106 |  | 
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| 107 |   public : | 
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| 108 |  | 
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| 109 |  | 
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| 110 |    MinCostFlow(Graph& _graph, CostMap& _cost, SupplyDemandMap& _supply_demand): | 
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| 111 |      graph(_graph),  | 
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| 112 |      cost(_cost),  | 
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| 113 |      supply_demand(_supply_demand),  | 
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| 114 |      flow(_graph),  | 
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| 115 |      potential(_graph){ } | 
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| 116 |  | 
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| 117 |      | 
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| 118 |     ///Runs the algorithm. | 
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| 119 |  | 
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| 120 |     ///Runs the algorithm. | 
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| 121 |  | 
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| 122 |     ///\todo May be it does make sense to be able to start with a nonzero  | 
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| 123 |     /// feasible primal-dual solution pair as well. | 
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| 124 |     void run() { | 
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| 125 |  | 
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| 126 |       //To store excess-deficit values | 
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| 127 |       SupplyDemandMap excess_deficit(graph); | 
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| 128 |  | 
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| 129 |       //Resetting variables from previous runs | 
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| 130 |       //total_cost = 0; | 
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| 131 |  | 
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| 132 |  | 
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| 133 |       typedef typename Graph::template NodeMap<int> HeapMap; | 
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| 134 |       typedef BinHeap< Node, SupplyDemand, typename Graph::template NodeMap<int>, | 
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| 135 |         std::greater<SupplyDemand> >    HeapType; | 
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| 136 |  | 
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| 137 |       //A heap for the excess nodes | 
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| 138 |       HeapMap excess_nodes_map(graph,-1); | 
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| 139 |       HeapType excess_nodes(excess_nodes_map); | 
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| 140 |  | 
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| 141 |       //A heap for the deficit nodes | 
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| 142 |       HeapMap deficit_nodes_map(graph,-1); | 
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| 143 |       HeapType deficit_nodes(deficit_nodes_map); | 
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| 144 |  | 
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| 145 |       //A container to store nonabundant arcs | 
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| 146 |       std::list<Edge> nonabundant_arcs; | 
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| 147 |  | 
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| 148 |          | 
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| 149 |       FOR_EACH_LOC(typename Graph::EdgeIt, e, graph){ | 
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| 150 |         flow.set(e,0); | 
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| 151 |         nonabundant_arcs.push_back(e); | 
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| 152 |       } | 
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| 153 |  | 
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| 154 |       //Initial value for delta | 
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| 155 |       SupplyDemand delta = 0; | 
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| 156 |  | 
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| 157 |       typedef UnionFindEnum<Node, Graph::template NodeMap> UFE; | 
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| 158 |  | 
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| 159 |       //A union-find structure to store the abundant components | 
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| 160 |       typename UFE::MapType abund_comp_map(graph); | 
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| 161 |       UFE abundant_components(abund_comp_map); | 
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| 162 |  | 
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| 163 |  | 
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| 164 |  | 
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| 165 |       FOR_EACH_LOC(typename Graph::NodeIt, n, graph){ | 
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| 166 |         excess_deficit.set(n,supply_demand[n]); | 
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| 167 |         //A supply node | 
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| 168 |         if (excess_deficit[n] > 0){ | 
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| 169 |           excess_nodes.push(n,excess_deficit[n]); | 
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| 170 |         } | 
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| 171 |         //A demand node | 
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| 172 |         if (excess_deficit[n] < 0){ | 
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| 173 |           deficit_nodes.push(n, - excess_deficit[n]); | 
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| 174 |         } | 
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| 175 |         //Finding out starting value of delta | 
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| 176 |         if (delta < abs(excess_deficit[n])){ | 
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| 177 |           delta = abs(excess_deficit[n]); | 
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| 178 |         } | 
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| 179 |         //Initialize the copy of the Dijkstra potential to zero | 
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| 180 |         potential.set(n,0); | 
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| 181 |         //Every single point is an abundant component initially  | 
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| 182 |         abundant_components.insert(n); | 
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| 183 |       } | 
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| 184 |  | 
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| 185 |       //It'll be allright as an initial value, though this value  | 
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| 186 |       //can be the maximum deficit here | 
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| 187 |       SupplyDemand max_excess = delta; | 
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| 188 |        | 
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| 189 |       ///\bug This is a serious cheat here, before we have an uncapacitated ResGraph | 
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| 190 |       ConstEdgeMap const_inf_map(MAXINT); | 
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| 191 |        | 
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| 192 |       //We need a residual graph which is uncapacitated | 
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| 193 |       ResGraph res_graph(graph, const_inf_map, flow); | 
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| 194 |        | 
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| 195 |       //An EdgeMap to tell which arcs are abundant | 
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| 196 |       typename Graph::template EdgeMap<bool> abundant_arcs(graph); | 
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| 197 |  | 
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| 198 |       //Let's construct the sugraph consisting only of the abundant edges | 
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| 199 |       typedef ConstMap< typename Graph::Node, bool > ConstNodeMap; | 
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| 200 |  | 
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| 201 |       ConstNodeMap const_true_map(true); | 
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| 202 |       typedef SubGraphWrapper< const Graph, ConstNodeMap,  | 
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| 203 |          typename Graph::template EdgeMap<bool> >  | 
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| 204 |         AbundantGraph; | 
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| 205 |       AbundantGraph abundant_graph(graph, const_true_map, abundant_arcs ); | 
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| 206 |        | 
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| 207 |       //Let's construct the residual graph for the abundant graph | 
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| 208 |       typedef ResGraphWrapper<const AbundantGraph,int,ConstEdgeMap,FlowMap>  | 
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| 209 |         ResAbGraph; | 
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| 210 |       //Again uncapacitated | 
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| 211 |       ResAbGraph res_ab_graph(abundant_graph, const_inf_map, flow); | 
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| 212 |        | 
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| 213 |       //We need things for the bfs | 
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| 214 |       typename ResAbGraph::template NodeMap<bool> bfs_reached(res_ab_graph); | 
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| 215 |       typename ResAbGraph::template NodeMap<typename ResAbGraph::Edge>  | 
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| 216 |         bfs_pred(res_ab_graph);  | 
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| 217 |       NullMap<typename ResAbGraph::Node, int> bfs_dist_dummy; | 
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| 218 |       //Teszt celbol: | 
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| 219 |       //BfsIterator<ResAbGraph, typename ResAbGraph::template NodeMap<bool> >  | 
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| 220 |       //izebize(res_ab_graph, bfs_reached); | 
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| 221 |       //We want to run bfs-es (more) on this graph 'res_ab_graph' | 
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| 222 |       Bfs < const ResAbGraph ,  | 
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| 223 |         typename ResAbGraph::template NodeMap<bool>,  | 
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| 224 |         typename ResAbGraph::template NodeMap<typename ResAbGraph::Edge>, | 
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| 225 |         NullMap<typename ResAbGraph::Node, int> >  | 
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| 226 |         bfs(res_ab_graph, bfs_reached, bfs_pred, bfs_dist_dummy); | 
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| 227 |       /*This is what Marci wants for a bfs | 
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| 228 |         template <typename Graph,  | 
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| 229 |             typename ReachedMap=typename Graph::template NodeMap<bool>,  | 
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| 230 |             typename PredMap | 
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| 231 |             =typename Graph::template NodeMap<typename Graph::Edge>,  | 
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| 232 |             typename DistMap=typename Graph::template NodeMap<int> >  | 
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| 233 |             class Bfs : public BfsIterator<Graph, ReachedMap> { | 
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| 234 |  | 
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| 235 |        */ | 
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| 236 |        | 
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| 237 |       ModCostMap mod_cost(res_graph, cost, potential); | 
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| 238 |  | 
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| 239 |       Dijkstra<ResGraph, ModCostMap> dijkstra(res_graph, mod_cost); | 
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| 240 |  | 
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| 241 |       //We will use the number of the nodes of the graph often | 
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| 242 |       int number_of_nodes = graph.nodeNum(); | 
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| 243 |  | 
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| 244 |       while (max_excess > 0){ | 
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| 245 |  | 
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| 246 |         //Reset delta if still too big | 
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| 247 |         if (8*number_of_nodes*max_excess <= delta){ | 
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| 248 |           delta = max_excess; | 
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| 249 |            | 
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| 250 |         } | 
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| 251 |  | 
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| 252 |         /* | 
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| 253 |          * Beginning of the delta scaling phase  | 
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| 254 |         */ | 
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| 255 |         //Merge and stuff | 
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| 256 |         { | 
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| 257 |           SupplyDemand buf=8*number_of_nodes*delta; | 
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| 258 |           typename std::list<Edge>::iterator i = nonabundant_arcs.begin(); | 
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| 259 |           while ( i != nonabundant_arcs.end() ){ | 
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| 260 |             if (flow[*i]>=buf){ | 
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| 261 |               Node a = abundant_components.find(res_graph.head(*i)); | 
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| 262 |               Node b = abundant_components.find(res_graph.tail(*i)); | 
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| 263 |               //Merge | 
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| 264 |               if (a != b){ | 
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| 265 |                 abundant_components.join(a,b); | 
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| 266 |                 //We want to push the smaller | 
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| 267 |                 //Which has greater absolut value excess/deficit | 
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| 268 |                 Node root=(abs(excess_deficit[a])>abs(excess_deficit[b]))?a:b; | 
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| 269 |                 //Which is the other | 
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| 270 |                 Node non_root = ( a == root ) ? b : a ; | 
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| 271 |                 abundant_components.makeRep(root); | 
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| 272 |                 SupplyDemand qty_to_augment = abs(excess_deficit[non_root]);  | 
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| 273 |                 //Push the positive value | 
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| 274 |                 if (excess_deficit[non_root] < 0) | 
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| 275 |                   swap(root, non_root); | 
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| 276 |                 //If the non_root node has excess/deficit at all | 
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| 277 |                 if (qty_to_augment>0){ | 
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| 278 |                   //Find path and augment | 
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| 279 |                   bfs.run(typename AbundantGraph::Node(non_root)); | 
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| 280 |                   //root should be reached | 
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| 281 |                    | 
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| 282 |                   //Augmenting on the found path | 
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| 283 |                   Node n=root; | 
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| 284 |                   ResGraphEdge e; | 
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| 285 |                   while (n!=non_root){ | 
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| 286 |                     e = bfs_pred[n]; | 
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| 287 |                     n = res_graph.tail(e); | 
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| 288 |                     res_graph.augment(e,qty_to_augment); | 
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| 289 |                   } | 
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| 290 |            | 
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| 291 |                   //We know that non_root had positive excess | 
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| 292 |                   excess_nodes.set(non_root, | 
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| 293 |                                    excess_nodes[non_root] - qty_to_augment); | 
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| 294 |                   //But what about root node | 
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| 295 |                   //It might have been positive and so became larger | 
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| 296 |                   if (excess_deficit[root]>0){ | 
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| 297 |                     excess_nodes.set(root,  | 
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| 298 |                                      excess_nodes[root] + qty_to_augment); | 
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| 299 |                   } | 
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| 300 |                   else{ | 
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| 301 |                     //Or negative but not turned into positive | 
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| 302 |                     deficit_nodes.set(root,  | 
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| 303 |                                       deficit_nodes[root] - qty_to_augment); | 
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| 304 |                   } | 
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| 305 |  | 
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| 306 |                   //Update the excess_deficit map | 
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| 307 |                   excess_deficit[non_root] -= qty_to_augment; | 
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| 308 |                   excess_deficit[root] += qty_to_augment; | 
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| 309 |  | 
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| 310 |                    | 
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| 311 |                 } | 
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| 312 |               } | 
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| 313 |               //What happens to i? | 
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| 314 |               //Marci and Zsolt says I shouldn't do such things | 
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| 315 |               nonabundant_arcs.erase(i++); | 
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| 316 |               abundant_arcs[*i] = true; | 
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| 317 |             } | 
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| 318 |             else | 
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| 319 |               ++i; | 
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| 320 |           } | 
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| 321 |         } | 
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| 322 |  | 
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| 323 |  | 
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| 324 |         Node s = excess_nodes.top();  | 
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| 325 |         max_excess = excess_nodes[s]; | 
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| 326 |         Node t = deficit_nodes.top();  | 
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| 327 |         if (max_excess < deficit_nodes[t]){ | 
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| 328 |           max_excess = deficit_nodes[t]; | 
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| 329 |         } | 
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| 330 |  | 
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| 331 |  | 
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| 332 |         while(max_excess > (number_of_nodes-1)*delta/number_of_nodes){ | 
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| 333 |            | 
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| 334 |            | 
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| 335 |           //s es t valasztasa | 
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| 336 |            | 
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| 337 |           //Dijkstra part        | 
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| 338 |           dijkstra.run(s); | 
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| 339 |            | 
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| 340 |           /*We know from theory that t can be reached | 
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| 341 |           if (!dijkstra.reached(t)){ | 
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| 342 |             //There are no k paths from s to t | 
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| 343 |             break; | 
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| 344 |           }; | 
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| 345 |           */ | 
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| 346 |            | 
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| 347 |           //We have to change the potential | 
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| 348 |           FOR_EACH_LOC(typename ResGraph::NodeIt, n, res_graph){ | 
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| 349 |             potential[n] += dijkstra.distMap()[n]; | 
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| 350 |           } | 
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| 351 |  | 
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| 352 |  | 
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| 353 |           //Augmenting on the sortest path | 
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| 354 |           Node n=t; | 
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| 355 |           ResGraphEdge e; | 
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| 356 |           while (n!=s){ | 
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| 357 |             e = dijkstra.pred(n); | 
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| 358 |             n = dijkstra.predNode(n); | 
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| 359 |             res_graph.augment(e,delta); | 
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| 360 |             /* | 
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| 361 |             //Let's update the total cost | 
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| 362 |             if (res_graph.forward(e)) | 
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| 363 |               total_cost += cost[e]; | 
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| 364 |             else  | 
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| 365 |               total_cost -= cost[e];         | 
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| 366 |             */ | 
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| 367 |           } | 
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| 368 |            | 
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| 369 |           //Update the excess_deficit map | 
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| 370 |           excess_deficit[s] -= delta; | 
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| 371 |           excess_deficit[t] += delta; | 
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| 372 |            | 
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| 373 |  | 
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| 374 |           //Update the excess_nodes heap | 
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| 375 |           if (delta > excess_nodes[s]){ | 
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| 376 |             if (delta > excess_nodes[s]) | 
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| 377 |               deficit_nodes.push(s,delta - excess_nodes[s]); | 
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| 378 |             excess_nodes.pop(); | 
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| 379 |              | 
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| 380 |           }  | 
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| 381 |           else{ | 
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| 382 |             excess_nodes.set(s, excess_nodes[s] - delta); | 
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| 383 |           } | 
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| 384 |           //Update the deficit_nodes heap | 
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| 385 |           if (delta > deficit_nodes[t]){ | 
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| 386 |             if (delta > deficit_nodes[t]) | 
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| 387 |               excess_nodes.push(t,delta - deficit_nodes[t]); | 
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| 388 |             deficit_nodes.pop(); | 
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| 389 |              | 
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| 390 |           }  | 
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| 391 |           else{ | 
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| 392 |             deficit_nodes.set(t, deficit_nodes[t] - delta); | 
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| 393 |           } | 
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| 394 |           //Dijkstra part ends here | 
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| 395 |            | 
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| 396 |           //Choose s and t again | 
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| 397 |           s = excess_nodes.top();  | 
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| 398 |           max_excess = excess_nodes[s]; | 
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| 399 |           t = deficit_nodes.top();  | 
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| 400 |           if (max_excess < deficit_nodes[t]){ | 
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| 401 |             max_excess = deficit_nodes[t]; | 
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| 402 |           } | 
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| 403 |  | 
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| 404 |         } | 
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| 405 |  | 
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| 406 |         /* | 
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| 407 |          * End of the delta scaling phase  | 
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| 408 |         */ | 
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| 409 |  | 
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| 410 |         //Whatever this means | 
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| 411 |         delta = delta / 2; | 
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| 412 |  | 
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| 413 |         /*This is not necessary here | 
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| 414 |         //Update the max_excess | 
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| 415 |         max_excess = 0; | 
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| 416 |         FOR_EACH_LOC(typename Graph::NodeIt, n, graph){ | 
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| 417 |           if (max_excess < excess_deficit[n]){ | 
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| 418 |             max_excess = excess_deficit[n]; | 
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| 419 |           } | 
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| 420 |         } | 
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| 421 |         */ | 
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| 422 |  | 
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| 423 |            | 
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| 424 |       }//while(max_excess > 0) | 
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| 425 |        | 
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| 426 |  | 
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| 427 |       //return i; | 
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| 428 |     } | 
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| 429 |  | 
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| 430 |  | 
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| 431 |  | 
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| 432 |  | 
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| 433 |     ///This function gives back the total cost of the found paths. | 
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| 434 |     ///Assumes that \c run() has been run and nothing changed since then. | 
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| 435 |     Cost totalCost(){ | 
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| 436 |       return total_cost; | 
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| 437 |     } | 
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| 438 |  | 
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| 439 |     ///Returns a const reference to the EdgeMap \c flow. \pre \ref run() must | 
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| 440 |     ///be called before using this function. | 
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| 441 |     const FlowMap &getFlow() const { return flow;} | 
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| 442 |  | 
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| 443 |   ///Returns a const reference to the NodeMap \c potential (the dual solution). | 
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| 444 |     /// \pre \ref run() must be called before using this function. | 
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| 445 |     const PotentialMap &getPotential() const { return potential;} | 
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| 446 |  | 
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| 447 |     ///This function checks, whether the given solution is optimal | 
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| 448 |     ///Running after a \c run() should return with true | 
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| 449 |     ///In this "state of the art" this only checks optimality, doesn't bother with feasibility | 
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| 450 |     /// | 
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| 451 |     ///\todo Is this OK here? | 
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| 452 |     bool checkComplementarySlackness(){ | 
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| 453 |       Cost mod_pot; | 
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| 454 |       Cost fl_e; | 
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| 455 |       FOR_EACH_LOC(typename Graph::EdgeIt, e, graph){ | 
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| 456 |         //C^{\Pi}_{i,j} | 
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| 457 |         mod_pot = cost[e]-potential[graph.head(e)]+potential[graph.tail(e)]; | 
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| 458 |         fl_e = flow[e]; | 
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| 459 |         //      std::cout << fl_e << std::endl; | 
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| 460 |         if (mod_pot > 0 && fl_e != 0) | 
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| 461 |           return false; | 
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| 462 |  | 
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| 463 |       } | 
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| 464 |       return true; | 
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| 465 |     } | 
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| 466 |  | 
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| 467 |     /* | 
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| 468 |     //For testing purposes only | 
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| 469 |     //Lists the node_properties | 
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| 470 |     void write_property_vector(const SupplyDemandMap& a, | 
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| 471 |                                char* prop_name="property"){ | 
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| 472 |       FOR_EACH_LOC(typename Graph::NodeIt, i, graph){ | 
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| 473 |         cout<<"Node id.: "<<graph.id(i)<<", "<<prop_name<<" value: "<<a[i]<<endl; | 
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| 474 |       } | 
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| 475 |       cout<<endl; | 
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| 476 |     } | 
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| 477 |     */ | 
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| 478 |     bool checkFeasibility(){ | 
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| 479 |       SupplyDemandMap supdem(graph); | 
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| 480 |       FOR_EACH_LOC(typename Graph::EdgeIt, e, graph){ | 
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| 481 |  | 
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| 482 |         if ( flow[e] < 0){ | 
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| 483 |  | 
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| 484 |           return false; | 
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| 485 |         } | 
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| 486 |         supdem[graph.tail(e)] += flow[e]; | 
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| 487 |         supdem[graph.head(e)] -= flow[e]; | 
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| 488 |       } | 
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| 489 |       //write_property_vector(supdem, "supdem"); | 
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| 490 |       //write_property_vector(supply_demand, "supply_demand"); | 
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| 491 |  | 
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| 492 |       FOR_EACH_LOC(typename Graph::NodeIt, n, graph){ | 
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| 493 |  | 
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| 494 |         if ( supdem[n] != supply_demand[n]){ | 
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| 495 |           //cout<<"Node id.: "<<graph.id(n)<<" : "<<supdem[n]<<", should be: "<<supply_demand[n]<<endl; | 
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| 496 |           return false; | 
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| 497 |         } | 
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| 498 |       } | 
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| 499 |  | 
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| 500 |       return true; | 
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| 501 |     } | 
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| 502 |  | 
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| 503 |     bool checkOptimality(){ | 
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| 504 |       return checkFeasibility() && checkComplementarySlackness(); | 
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| 505 |     } | 
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| 506 |  | 
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| 507 |   }; //class MinCostFlow | 
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| 508 |  | 
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| 509 |   ///@} | 
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| 510 |  | 
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| 511 | } //namespace hugo | 
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| 512 |  | 
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| 513 | #endif //HUGO_MINCOSTFLOW_H | 
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