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// -*- c++ -*-
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#ifndef HUGO_MINCOSTFLOWS_H
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#define HUGO_MINCOSTFLOWS_H
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///\ingroup galgs
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///\file
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///\brief An algorithm for finding a flow of value \c k (for small values of \c k) having minimal total cost
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#include <hugo/dijkstra.h>
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#include <hugo/graph_wrapper.h>
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#include <hugo/maps.h>
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#include <vector>
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#include <for_each_macros.h>
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namespace hugo {
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/// \addtogroup galgs
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/// @{
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///\brief Implementation of an algorithm for finding a flow of value \c k
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///(for small values of \c k) having minimal total cost between 2 nodes
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///
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///
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/// The class \ref hugo::MinCostFlows "MinCostFlows" implements
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/// an algorithm for finding a flow of value \c k
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///(for small values of \c k) having minimal total cost
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/// from a given source node to a given target node in an
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/// edge-weighted directed graph having nonnegative integer capacities.
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/// The range of the length (weight) function is nonnegative reals but
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/// the range of capacity function is the set of nonnegative integers.
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/// It is not a polinomial time algorithm for counting the minimum cost
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/// maximal flow, since it counts the minimum cost flow for every value 0..M
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/// where \c M is the value of the maximal flow.
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///
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///\author Attila Bernath
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template <typename Graph, typename LengthMap, typename CapacityMap>
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class MinCostFlows {
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typedef typename LengthMap::ValueType Length;
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//Warning: this should be integer type
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typedef typename CapacityMap::ValueType Capacity;
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typedef typename Graph::Node Node;
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typedef typename Graph::NodeIt NodeIt;
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typedef typename Graph::Edge Edge;
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typedef typename Graph::OutEdgeIt OutEdgeIt;
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typedef typename Graph::template EdgeMap<int> EdgeIntMap;
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// typedef ConstMap<Edge,int> ConstMap;
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typedef ResGraphWrapper<const Graph,int,CapacityMap,EdgeIntMap> ResGraphType;
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typedef typename ResGraphType::Edge ResGraphEdge;
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class ModLengthMap {
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//typedef typename ResGraphType::template NodeMap<Length> NodeMap;
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typedef typename Graph::template NodeMap<Length> NodeMap;
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const ResGraphType& G;
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// const EdgeIntMap& rev;
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const LengthMap &ol;
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const NodeMap &pot;
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public :
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typedef typename LengthMap::KeyType KeyType;
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typedef typename LengthMap::ValueType ValueType;
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ValueType operator[](typename ResGraphType::Edge e) const {
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if (G.forward(e))
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return ol[e]-(pot[G.head(e)]-pot[G.tail(e)]);
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else
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return -ol[e]-(pot[G.head(e)]-pot[G.tail(e)]);
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}
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ModLengthMap(const ResGraphType& _G,
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const LengthMap &o, const NodeMap &p) :
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G(_G), /*rev(_rev),*/ ol(o), pot(p){};
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};//ModLengthMap
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protected:
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//Input
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const Graph& G;
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const LengthMap& length;
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const CapacityMap& capacity;
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//auxiliary variables
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//To store the flow
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EdgeIntMap flow;
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//To store the potentila (dual variables)
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typename Graph::template NodeMap<Length> potential;
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Length total_length;
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public :
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MinCostFlows(Graph& _G, LengthMap& _length, CapacityMap& _cap) : G(_G),
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length(_length), capacity(_cap), flow(_G), potential(_G){ }
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///Runs the algorithm.
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///Runs the algorithm.
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///Returns k if there are at least k edge-disjoint paths from s to t.
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///Otherwise it returns the number of found edge-disjoint paths from s to t.
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///\todo May be it does make sense to be able to start with a nonzero
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/// feasible primal-dual solution pair as well.
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int run(Node s, Node t, int k) {
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//Resetting variables from previous runs
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total_length = 0;
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FOR_EACH_LOC(typename Graph::EdgeIt, e, G){
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flow.set(e,0);
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}
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//Initialize the potential to zero
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FOR_EACH_LOC(typename Graph::NodeIt, n, G){
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potential.set(n,0);
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}
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//We need a residual graph
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ResGraphType res_graph(G, capacity, flow);
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ModLengthMap mod_length(res_graph, length, potential);
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Dijkstra<ResGraphType, ModLengthMap> dijkstra(res_graph, mod_length);
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int i;
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for (i=0; i<k; ++i){
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dijkstra.run(s);
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if (!dijkstra.reached(t)){
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//There are no k paths from s to t
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break;
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};
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//We have to change the potential
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FOR_EACH_LOC(typename ResGraphType::NodeIt, n, res_graph){
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potential[n] += dijkstra.distMap()[n];
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}
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//Augmenting on the sortest path
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Node n=t;
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ResGraphEdge e;
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while (n!=s){
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e = dijkstra.pred(n);
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n = dijkstra.predNode(n);
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res_graph.augment(e,1);
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//Let's update the total length
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if (res_graph.forward(e))
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total_length += length[e];
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else
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total_length -= length[e];
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}
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}
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return i;
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}
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///This function gives back the total length of the found paths.
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///Assumes that \c run() has been run and nothing changed since then.
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Length totalLength(){
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return total_length;
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}
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///Returns a const reference to the EdgeMap \c flow. \pre \ref run() must
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///be called before using this function.
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const EdgeIntMap &getFlow() const { return flow;}
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///Returns a const reference to the NodeMap \c potential (the dual solution).
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/// \pre \ref run() must be called before using this function.
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const EdgeIntMap &getPotential() const { return potential;}
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///This function checks, whether the given solution is optimal
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///Running after a \c run() should return with true
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///In this "state of the art" this only check optimality, doesn't bother with feasibility
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///
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///\todo Is this OK here?
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bool checkComplementarySlackness(){
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Length mod_pot;
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Length fl_e;
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FOR_EACH_LOC(typename Graph::EdgeIt, e, G){
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//C^{\Pi}_{i,j}
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mod_pot = length[e]-potential[G.head(e)]+potential[G.tail(e)];
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fl_e = flow[e];
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// std::cout << fl_e << std::endl;
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if (0<fl_e && fl_e<capacity[e]){
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if (mod_pot != 0)
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return false;
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}
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else{
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if (mod_pot > 0 && fl_e != 0)
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return false;
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if (mod_pot < 0 && fl_e != capacity[e])
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return false;
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}
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}
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return true;
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}
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}; //class MinCostFlows
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///@}
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} //namespace hugo
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#endif //HUGO_MINCOSTFLOWS_H
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