| 1 | // -*- c++ -*- | 
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| 2 | #ifndef LEMON_MINCOSTFLOW_H | 
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| 3 | #define LEMON_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 <lemon/dijkstra.h> | 
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| 10 | #include <lemon/graph_wrapper.h> | 
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| 11 | #include <lemon/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 <lemon/for_each_macros.h> | 
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| 16 | #include <lemon/unionfind.h> | 
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| 17 | #include <lemon/bin_heap.h> | 
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| 18 | #include <bfs_dfs.h> | 
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| 19 |  | 
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| 20 | namespace lemon { | 
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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 lemon::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 lemon | 
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| 512 |  | 
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| 513 | #endif //LEMON_MINCOSTFLOW_H | 
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