src/hugo/mincostflows.h
author alpar
Mon, 13 Sep 2004 11:24:35 +0000
changeset 835 eb9587f09b42
parent 785 a9b0863c2265
child 860 3577b3db6089
permissions -rw-r--r--
Remove one remaining range checking.
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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 flowalgs
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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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namespace hugo {
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/// \addtogroup flowalgs
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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 potential (dual variables)
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    typedef typename Graph::template NodeMap<Length> PotentialMap;
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    PotentialMap 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 (typename Graph::EdgeIt e(G); e!=INVALID; ++e) flow.set(e, 0);
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      //Initialize the potential to zero
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      for (typename Graph::NodeIt n(G); n!=INVALID; ++n) potential.set(n, 0);
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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(typename ResGraphType::NodeIt n(res_graph); n!=INVALID; ++n)
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	  potential[n] += dijkstra.distMap()[n];
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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 PotentialMap &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(typename Graph::EdgeIt e(G); e!=INVALID; ++e) {
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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