| [610] | 1 | // -*- c++ -*- | 
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| [633] | 2 | #ifndef HUGO_MINCOSTFLOW_H | 
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 | 3 | #define HUGO_MINCOSTFLOW_H | 
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| [610] | 4 |  | 
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 | 5 | ///\ingroup galgs | 
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 | 6 | ///\file | 
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| [645] | 7 | ///\brief An algorithm for finding the minimum cost flow of given value in an uncapacitated network | 
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| [611] | 8 |  | 
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| [610] | 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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| [657] | 13 | #include <list> | 
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| [662] | 14 | #include <values.h> | 
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| [661] | 15 | #include <hugo/for_each_macros.h> | 
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 | 16 | #include <hugo/unionfind.h> | 
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| [662] | 17 | #include <hugo/bin_heap.h> | 
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 | 18 | #include <bfs_dfs.h> | 
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| [610] | 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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| [661] | 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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| [610] | 27 |   ///  | 
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 | 28 |   /// | 
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| [633] | 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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| [661] | 36 |   /// The range of the cost (weight) function is nonnegative reals but  | 
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| [610] | 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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| [661] | 43 |   template <typename Graph, typename CostMap, typename SupplyDemandMap> | 
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| [633] | 44 |   class MinCostFlow { | 
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| [610] | 45 |  | 
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| [661] | 46 |     typedef typename CostMap::ValueType Cost; | 
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| [610] | 47 |  | 
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| [633] | 48 |  | 
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| [635] | 49 |     typedef typename SupplyDemandMap::ValueType SupplyDemand; | 
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| [610] | 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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| [661] | 55 |     typedef typename Graph::template EdgeMap<SupplyDemand> FlowMap; | 
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 | 56 |     typedef ConstMap<Edge,SupplyDemand> ConstEdgeMap; | 
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| [610] | 57 |  | 
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 | 58 |     //    typedef ConstMap<Edge,int> ConstMap; | 
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 | 59 |  | 
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| [661] | 60 |     typedef ResGraphWrapper<const Graph,int,ConstEdgeMap,FlowMap> ResGraph; | 
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 | 61 |     typedef typename ResGraph::Edge ResGraphEdge; | 
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| [610] | 62 |  | 
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| [661] | 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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| [610] | 67 |       //      const EdgeIntMap& rev; | 
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| [661] | 68 |       const CostMap &ol; | 
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| [610] | 69 |       const NodeMap &pot; | 
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 | 70 |     public : | 
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| [661] | 71 |       typedef typename CostMap::KeyType KeyType; | 
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 | 72 |       typedef typename CostMap::ValueType ValueType; | 
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| [610] | 73 |          | 
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| [661] | 74 |       ValueType operator[](typename ResGraph::Edge e) const {      | 
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| [659] | 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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| [610] | 77 |         else | 
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| [659] | 78 |           return -ol[e]-(pot[res_graph.head(e)]-pot[res_graph.tail(e)]);    | 
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| [610] | 79 |       }      | 
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 | 80 |          | 
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| [661] | 81 |       ModCostMap(const ResGraph& _res_graph, | 
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 | 82 |                    const CostMap &o,  const NodeMap &p) :  | 
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| [659] | 83 |         res_graph(_res_graph), /*rev(_rev),*/ ol(o), pot(p){};  | 
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| [661] | 84 |     };//ModCostMap | 
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| [610] | 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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| [659] | 90 |     const Graph& graph; | 
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| [661] | 91 |     const CostMap& cost; | 
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| [635] | 92 |     const SupplyDemandMap& supply_demand;//supply or demand of nodes | 
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| [610] | 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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| [661] | 98 |     FlowMap flow;  | 
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| [662] | 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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| [610] | 102 |      | 
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 | 103 |  | 
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| [661] | 104 |     Cost total_cost; | 
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| [610] | 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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| [662] | 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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| [672] | 115 |      potential(_graph){ } | 
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| [610] | 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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| [635] | 121 |  | 
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| [610] | 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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| [659] | 124 |     void run() { | 
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| [610] | 125 |  | 
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| [672] | 126 |       //To store excess-deficit values | 
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 | 127 |       SupplyDemandMap excess_deficit(graph); | 
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 | 128 |  | 
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| [610] | 129 |       //Resetting variables from previous runs | 
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| [661] | 130 |       //total_cost = 0; | 
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| [635] | 131 |  | 
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| [672] | 132 |  | 
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| [635] | 133 |       typedef typename Graph::template NodeMap<int> HeapMap; | 
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| [662] | 134 |       typedef BinHeap< Node, SupplyDemand, typename Graph::template NodeMap<int>, | 
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| [635] | 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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| [659] | 138 |       HeapMap excess_nodes_map(graph,-1); | 
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| [635] | 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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| [659] | 142 |       HeapMap deficit_nodes_map(graph,-1); | 
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| [635] | 143 |       HeapType deficit_nodes(deficit_nodes_map); | 
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 | 144 |  | 
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| [657] | 145 |       //A container to store nonabundant arcs | 
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| [662] | 146 |       std::list<Edge> nonabundant_arcs; | 
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| [659] | 147 |  | 
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 | 148 |          | 
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 | 149 |       FOR_EACH_LOC(typename Graph::EdgeIt, e, graph){ | 
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| [610] | 150 |         flow.set(e,0); | 
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| [657] | 151 |         nonabundant_arcs.push_back(e); | 
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| [610] | 152 |       } | 
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| [633] | 153 |  | 
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 | 154 |       //Initial value for delta | 
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| [635] | 155 |       SupplyDemand delta = 0; | 
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 | 156 |  | 
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| [657] | 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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| [662] | 160 |       typename UFE::MapType abund_comp_map(graph); | 
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| [657] | 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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| [659] | 165 |       FOR_EACH_LOC(typename Graph::NodeIt, n, graph){ | 
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| [635] | 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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| [633] | 170 |         } | 
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| [635] | 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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| [633] | 179 |         //Initialize the copy of the Dijkstra potential to zero | 
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| [610] | 180 |         potential.set(n,0); | 
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| [657] | 181 |         //Every single point is an abundant component initially  | 
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 | 182 |         abundant_components.insert(n); | 
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| [610] | 183 |       } | 
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 | 184 |  | 
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| [635] | 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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| [610] | 188 |        | 
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| [661] | 189 |       ///\bug This is a serious cheat here, before we have an uncapacitated ResGraph | 
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| [662] | 190 |       ConstEdgeMap const_inf_map(MAXINT); | 
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| [661] | 191 |        | 
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| [633] | 192 |       //We need a residual graph which is uncapacitated | 
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| [661] | 193 |       ResGraph res_graph(graph, const_inf_map, flow); | 
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| [659] | 194 |        | 
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 | 195 |       //An EdgeMap to tell which arcs are abundant | 
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| [662] | 196 |       typename Graph::template EdgeMap<bool> abundant_arcs(graph); | 
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| [610] | 197 |  | 
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| [659] | 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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| [672] | 200 |  | 
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| [659] | 201 |       ConstNodeMap const_true_map(true); | 
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| [662] | 202 |       typedef SubGraphWrapper< const Graph, ConstNodeMap,  | 
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 | 203 |          typename Graph::template EdgeMap<bool> >  | 
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| [659] | 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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| [662] | 208 |       typedef ResGraphWrapper<const AbundantGraph,int,ConstEdgeMap,FlowMap>  | 
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| [659] | 209 |         ResAbGraph; | 
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 | 210 |       //Again uncapacitated | 
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| [661] | 211 |       ResAbGraph res_ab_graph(abundant_graph, const_inf_map, flow); | 
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| [659] | 212 |        | 
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 | 213 |       //We need things for the bfs | 
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| [662] | 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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| [659] | 216 |         bfs_pred(res_ab_graph);  | 
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| [662] | 217 |       NullMap<typename ResAbGraph::Node, int> bfs_dist_dummy; | 
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| [671] | 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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| [659] | 221 |       //We want to run bfs-es (more) on this graph 'res_ab_graph' | 
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| [671] | 222 |       Bfs < const ResAbGraph ,  | 
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| [662] | 223 |         typename ResAbGraph::template NodeMap<bool>,  | 
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 | 224 |         typename ResAbGraph::template NodeMap<typename ResAbGraph::Edge>, | 
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| [659] | 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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| [662] | 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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| [610] | 236 |        | 
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| [661] | 237 |       ModCostMap mod_cost(res_graph, cost, potential); | 
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| [610] | 238 |  | 
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| [661] | 239 |       Dijkstra<ResGraph, ModCostMap> dijkstra(res_graph, mod_cost); | 
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| [610] | 240 |  | 
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| [671] | 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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| [633] | 243 |  | 
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| [635] | 244 |       while (max_excess > 0){ | 
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 | 245 |  | 
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| [657] | 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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| [645] | 252 |         /* | 
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 | 253 |          * Beginning of the delta scaling phase  | 
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 | 254 |         */ | 
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| [635] | 255 |         //Merge and stuff | 
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| [657] | 256 |         { | 
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 | 257 |           SupplyDemand buf=8*number_of_nodes*delta; | 
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| [662] | 258 |           typename std::list<Edge>::iterator i = nonabundant_arcs.begin(); | 
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| [657] | 259 |           while ( i != nonabundant_arcs.end() ){ | 
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| [671] | 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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| [657] | 263 |               //Merge | 
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 | 264 |               if (a != b){ | 
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 | 265 |                 abundant_components.join(a,b); | 
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| [659] | 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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| [671] | 279 |                   bfs.run(typename AbundantGraph::Node(non_root)); | 
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| [659] | 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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| [671] | 286 |                     e = bfs_pred[n]; | 
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| [659] | 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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| [671] | 292 |                   excess_nodes.set(non_root, | 
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 | 293 |                                    excess_nodes[non_root] - qty_to_augment); | 
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| [659] | 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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| [671] | 297 |                     excess_nodes.set(root,  | 
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 | 298 |                                      excess_nodes[root] + qty_to_augment); | 
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| [659] | 299 |                   } | 
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 | 300 |                   else{ | 
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 | 301 |                     //Or negative but not turned into positive | 
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| [671] | 302 |                     deficit_nodes.set(root,  | 
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 | 303 |                                       deficit_nodes[root] - qty_to_augment); | 
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| [659] | 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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| [657] | 312 |               } | 
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 | 313 |               //What happens to i? | 
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| [659] | 314 |               //Marci and Zsolt says I shouldn't do such things | 
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 | 315 |               nonabundant_arcs.erase(i++); | 
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| [671] | 316 |               abundant_arcs[*i] = true; | 
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| [657] | 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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| [635] | 323 |  | 
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 | 324 |         Node s = excess_nodes.top();  | 
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| [672] | 325 |         max_excess = excess_nodes[s]; | 
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| [635] | 326 |         Node t = deficit_nodes.top();  | 
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| [659] | 327 |         if (max_excess < deficit_nodes[t]){ | 
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 | 328 |           max_excess = deficit_nodes[t]; | 
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| [635] | 329 |         } | 
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 | 330 |  | 
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 | 331 |  | 
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| [662] | 332 |         while(max_excess > (number_of_nodes-1)*delta/number_of_nodes){ | 
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| [659] | 333 |            | 
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| [635] | 334 |            | 
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 | 335 |           //s es t valasztasa | 
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| [659] | 336 |            | 
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| [635] | 337 |           //Dijkstra part        | 
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 | 338 |           dijkstra.run(s); | 
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| [659] | 339 |            | 
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| [635] | 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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| [661] | 348 |           FOR_EACH_LOC(typename ResGraph::NodeIt, n, res_graph){ | 
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| [635] | 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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| [661] | 361 |             //Let's update the total cost | 
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| [635] | 362 |             if (res_graph.forward(e)) | 
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| [661] | 363 |               total_cost += cost[e]; | 
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| [635] | 364 |             else  | 
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| [661] | 365 |               total_cost -= cost[e];         | 
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| [635] | 366 |             */ | 
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 | 367 |           } | 
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| [659] | 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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| [635] | 373 |  | 
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 | 374 |           //Update the excess_nodes heap | 
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| [672] | 375 |           if (delta > excess_nodes[s]){ | 
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| [635] | 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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| [671] | 382 |             excess_nodes.set(s, excess_nodes[s] - delta); | 
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| [635] | 383 |           } | 
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 | 384 |           //Update the deficit_nodes heap | 
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| [672] | 385 |           if (delta > deficit_nodes[t]){ | 
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| [635] | 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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| [671] | 392 |             deficit_nodes.set(t, deficit_nodes[t] - delta); | 
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| [635] | 393 |           } | 
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 | 394 |           //Dijkstra part ends here | 
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| [659] | 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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| [633] | 404 |         } | 
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 | 405 |  | 
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 | 406 |         /* | 
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| [635] | 407 |          * End of the delta scaling phase  | 
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 | 408 |         */ | 
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| [633] | 409 |  | 
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| [635] | 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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| [659] | 416 |         FOR_EACH_LOC(typename Graph::NodeIt, n, graph){ | 
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| [635] | 417 |           if (max_excess < excess_deficit[n]){ | 
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 | 418 |             max_excess = excess_deficit[n]; | 
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| [610] | 419 |           } | 
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 | 420 |         } | 
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| [633] | 421 |         */ | 
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| [657] | 422 |  | 
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| [610] | 423 |            | 
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| [635] | 424 |       }//while(max_excess > 0) | 
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| [610] | 425 |        | 
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 | 426 |  | 
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| [671] | 427 |       //return i; | 
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| [610] | 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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| [661] | 433 |     ///This function gives back the total cost of the found paths. | 
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| [610] | 434 |     ///Assumes that \c run() has been run and nothing changed since then. | 
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| [661] | 435 |     Cost totalCost(){ | 
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 | 436 |       return total_cost; | 
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| [610] | 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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| [662] | 441 |     const FlowMap &getFlow() const { return flow;} | 
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| [610] | 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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| [662] | 445 |     const PotentialMap &getPotential() const { return potential;} | 
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| [610] | 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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| [672] | 449 |     ///In this "state of the art" this only checks optimality, doesn't bother with feasibility | 
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| [610] | 450 |     /// | 
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 | 451 |     ///\todo Is this OK here? | 
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 | 452 |     bool checkComplementarySlackness(){ | 
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| [661] | 453 |       Cost mod_pot; | 
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 | 454 |       Cost fl_e; | 
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| [659] | 455 |       FOR_EACH_LOC(typename Graph::EdgeIt, e, graph){ | 
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| [610] | 456 |         //C^{\Pi}_{i,j} | 
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| [661] | 457 |         mod_pot = cost[e]-potential[graph.head(e)]+potential[graph.tail(e)]; | 
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| [610] | 458 |         fl_e = flow[e]; | 
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 | 459 |         //      std::cout << fl_e << std::endl; | 
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| [672] | 460 |         if (mod_pot > 0 && fl_e != 0) | 
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 | 461 |           return false; | 
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 | 462 |  | 
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| [610] | 463 |       } | 
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 | 464 |       return true; | 
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 | 465 |     } | 
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| [672] | 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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| [610] | 506 |  | 
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| [633] | 507 |   }; //class MinCostFlow | 
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| [610] | 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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