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/* -*- C++ -*-
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*
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* This file is a part of LEMON, a generic C++ optimization library
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*
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* Copyright (C) 2003-2008
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* Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
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* (Egervary Research Group on Combinatorial Optimization, EGRES).
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*
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* Permission to use, modify and distribute this software is granted
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* provided that this copyright notice appears in all copies. For
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* precise terms see the accompanying LICENSE file.
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*
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* This software is provided "AS IS" with no warranty of any kind,
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* express or implied, and with no claim as to its suitability for any
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* purpose.
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*
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*/
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#ifndef LEMON_SSP_MIN_COST_FLOW_H
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#define LEMON_SSP_MIN_COST_FLOW_H
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///\ingroup min_cost_flow
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///
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///\file
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///\brief An algorithm for finding a flow of value \c k (for
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///small values of \c k) having minimal total cost
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#include <lemon/dijkstra.h>
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#include <lemon/graph_adaptor.h>
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#include <lemon/maps.h>
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#include <vector>
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namespace lemon {
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/// \addtogroup min_cost_flow
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/// @{
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/// \brief Implementation of an algorithm for finding a flow of
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/// value \c k (for small values of \c k) having minimal total cost
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/// between two nodes
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///
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///
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/// The \ref lemon::SspMinCostFlow "Successive Shortest Path Minimum
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/// Cost Flow" implements an algorithm for finding a flow of value
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/// \c k having minimal total cost from a given source node to a
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/// given target node in a directed graph with a cost function on
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/// the edges. To this end, the edge-capacities and edge-costs have
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/// to be nonnegative. The edge-capacities should be integers, but
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/// the edge-costs can be integers, reals or of other comparable
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/// numeric type. This algorithm is intended to be used only for
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/// small values of \c k, since it is only polynomial in k, not in
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/// the length of k (which is log k): in order to find the minimum
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/// cost flow of value \c k it finds the minimum cost flow of value
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/// \c i for every \c i between 0 and \c k.
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///
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///\param Graph The directed graph type the algorithm runs on.
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///\param LengthMap The type of the length map.
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///\param CapacityMap The capacity map type.
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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 SspMinCostFlow {
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typedef typename LengthMap::Value Length;
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//Warning: this should be integer type
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typedef typename CapacityMap::Value 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 ResGraphAdaptor<const Graph,int,CapacityMap,EdgeIntMap> ResGW;
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typedef typename ResGW::Edge ResGraphEdge;
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protected:
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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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EdgeIntMap flow;
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typedef typename Graph::template NodeMap<Length> PotentialMap;
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PotentialMap potential;
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Node s;
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Node t;
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Length total_length;
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class ModLengthMap {
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typedef typename Graph::template NodeMap<Length> NodeMap;
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const ResGW& g;
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const LengthMap &length;
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const NodeMap &pot;
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public :
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typedef typename LengthMap::Key Key;
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typedef typename LengthMap::Value Value;
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ModLengthMap(const ResGW& _g,
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const LengthMap &_length, const NodeMap &_pot) :
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g(_g), /*rev(_rev),*/ length(_length), pot(_pot) { }
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Value operator[](typename ResGW::Edge e) const {
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if (g.forward(e))
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return length[e]-(pot[g.target(e)]-pot[g.source(e)]);
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else
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return -length[e]-(pot[g.target(e)]-pot[g.source(e)]);
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}
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}; //ModLengthMap
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ResGW res_graph;
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ModLengthMap mod_length;
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Dijkstra<ResGW, ModLengthMap> dijkstra;
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public :
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/// \brief The constructor of the class.
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///
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/// \param _g The directed graph the algorithm runs on.
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/// \param _length The length (cost) of the edges.
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/// \param _cap The capacity of the edges.
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/// \param _s Source node.
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/// \param _t Target node.
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SspMinCostFlow(Graph& _g, LengthMap& _length, CapacityMap& _cap,
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Node _s, Node _t) :
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g(_g), length(_length), capacity(_cap), flow(_g), potential(_g),
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s(_s), t(_t),
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res_graph(g, capacity, flow),
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mod_length(res_graph, length, potential),
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dijkstra(res_graph, mod_length) {
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reset();
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}
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/// \brief Tries to augment the flow between s and t by 1. The
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/// return value shows if the augmentation is successful.
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bool augment() {
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dijkstra.run(s);
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if (!dijkstra.reached(t)) {
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//Unsuccessful augmentation.
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return false;
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} else {
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//We have to change the potential
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for(typename ResGW::NodeIt n(res_graph); n!=INVALID; ++n)
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potential.set(n, potential[n]+dijkstra.distMap()[n]);
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//Augmenting on the shortest 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.predEdge(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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return true;
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}
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}
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/// \brief Runs the algorithm.
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///
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/// Runs the algorithm.
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/// Returns k if there is a flow of value at least k from s to t.
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/// Otherwise it returns the maximum value of a flow from s to t.
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///
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/// \param k The value of the flow we are looking for.
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///
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/// \todo May be it does make sense to be able to start with a
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/// nonzero feasible primal-dual solution pair as well.
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///
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/// \todo If the current flow value is bigger than k, then
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/// everything is cleared and the algorithm starts from zero
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/// flow. Is it a good approach?
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int run(int k) {
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if (flowValue()>k) reset();
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while (flowValue()<k && augment()) { }
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return flowValue();
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}
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/// \brief The class is reset to zero flow and potential.
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void reset() {
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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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for (typename Graph::NodeIt n(g); n!=INVALID; ++n) potential.set(n, 0);
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}
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/// \brief Returns the value of the current flow.
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int flowValue() const {
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int i=0;
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for (typename Graph::OutEdgeIt e(g, s); e!=INVALID; ++e) i+=flow[e];
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for (typename Graph::InEdgeIt e(g, s); e!=INVALID; ++e) i-=flow[e];
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return i;
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}
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/// \brief Total cost of the found flow.
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///
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/// This function gives back the total cost of the found flow.
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Length totalLength(){
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return total_length;
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}
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/// \brief Returns a const reference to the EdgeMap \c flow.
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///
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/// Returns a const reference to the EdgeMap \c flow.
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const EdgeIntMap &getFlow() const { return flow;}
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/// \brief Returns a const reference to the NodeMap \c potential
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/// (the dual solution).
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///
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/// Returns a const reference to the NodeMap \c potential (the
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/// dual solution).
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const PotentialMap &getPotential() const { return potential;}
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/// \brief Checking the complementary slackness optimality criteria.
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///
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/// This function checks, whether the given flow and potential
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/// satisfy the complementary slackness conditions (i.e. these are optimal).
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/// This function only checks optimality, doesn't bother with feasibility.
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/// For testing purpose.
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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.target(e)]+potential[g.source(e)];
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fl_e = flow[e];
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if (0<fl_e && fl_e<capacity[e]) {
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/// \todo better comparison is needed for real types, moreover,
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/// this comparison here is superfluous.
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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 SspMinCostFlow
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///@}
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} //namespace lemon
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#endif //LEMON_SSP_MIN_COST_FLOW_H
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