# source:lemon-0.x/lemon/min_cost_flow.h@1755:bf267b301a5e

Last change on this file since 1755:bf267b301a5e was 1527:7ceab500e1f6, checked in by athos, 16 years ago

Doc review+corrections in my own documentation according to the reviewers comments.

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1/* -*- C++ -*-
2 * lemon/min_cost_flow.h - Part of LEMON, a generic C++ optimization library
3 *
4 * Copyright (C) 2005 Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
5 * (Egervary Research Group on Combinatorial Optimization, EGRES).
6 *
7 * Permission to use, modify and distribute this software is granted
8 * provided that this copyright notice appears in all copies. For
9 * precise terms see the accompanying LICENSE file.
10 *
11 * This software is provided "AS IS" with no warranty of any kind,
12 * express or implied, and with no claim as to its suitability for any
13 * purpose.
14 *
15 */
16
17#ifndef LEMON_MIN_COST_FLOW_H
18#define LEMON_MIN_COST_FLOW_H
19
20///\ingroup flowalgs
21///\file
22///\brief An algorithm for finding a flow of value \c k (for small values of \c k) having minimal total cost
23
24
25#include <lemon/dijkstra.h>
27#include <lemon/maps.h>
28#include <vector>
29
30namespace lemon {
31
33/// @{
34
35  ///\brief Implementation of an algorithm for finding a flow of value \c k
36  ///(for small values of \c k) having minimal total cost between 2 nodes
37  ///
38  ///
39  /// The class \ref lemon::MinCostFlow "MinCostFlow" implements an
40  /// algorithm for finding a flow of value \c k having minimal total
41  /// cost from a given source node to a given target node in a
42  /// directed graph with a cost function on the edges. To
43  /// this end, the edge-capacities and edge-costs have to be
44  /// nonnegative.  The edge-capacities should be integers, but the
45  /// edge-costs can be integers, reals or of other comparable
46  /// numeric type.  This algorithm is intended to be used only for
47  /// small values of \c k, since it is only polynomial in k, not in
48  /// the length of k (which is log k): in order to find the minimum
49  /// cost flow of value \c k it finds the minimum cost flow of value
50  /// \c i for every \c i between 0 and \c k.
51  ///
52  ///\param Graph The directed graph type the algorithm runs on.
53  ///\param LengthMap The type of the length map.
54  ///\param CapacityMap The capacity map type.
55  ///
56  ///\author Attila Bernath
57  template <typename Graph, typename LengthMap, typename CapacityMap>
58  class MinCostFlow {
59
60    typedef typename LengthMap::Value Length;
61
62    //Warning: this should be integer type
63    typedef typename CapacityMap::Value Capacity;
64
65    typedef typename Graph::Node Node;
66    typedef typename Graph::NodeIt NodeIt;
67    typedef typename Graph::Edge Edge;
68    typedef typename Graph::OutEdgeIt OutEdgeIt;
69    typedef typename Graph::template EdgeMap<int> EdgeIntMap;
70
72    typedef typename ResGW::Edge ResGraphEdge;
73
74  protected:
75
76    const Graph& g;
77    const LengthMap& length;
78    const CapacityMap& capacity;
79
80    EdgeIntMap flow;
81    typedef typename Graph::template NodeMap<Length> PotentialMap;
82    PotentialMap potential;
83
84    Node s;
85    Node t;
86
87    Length total_length;
88
89    class ModLengthMap {
90      typedef typename Graph::template NodeMap<Length> NodeMap;
91      const ResGW& g;
92      const LengthMap &length;
93      const NodeMap &pot;
94    public :
95      typedef typename LengthMap::Key Key;
96      typedef typename LengthMap::Value Value;
97
98      ModLengthMap(const ResGW& _g,
99                   const LengthMap &_length, const NodeMap &_pot) :
100        g(_g), /*rev(_rev),*/ length(_length), pot(_pot) { }
101
102      Value operator[](typename ResGW::Edge e) const {
103        if (g.forward(e))
104          return  length[e]-(pot[g.target(e)]-pot[g.source(e)]);
105        else
106          return -length[e]-(pot[g.target(e)]-pot[g.source(e)]);
107      }
108
109    }; //ModLengthMap
110
111    ResGW res_graph;
112    ModLengthMap mod_length;
113    Dijkstra<ResGW, ModLengthMap> dijkstra;
114
115  public :
116
117    /*! \brief The constructor of the class.
118
119    \param _g The directed graph the algorithm runs on.
120    \param _length The length (cost) of the edges.
121    \param _cap The capacity of the edges.
122    \param _s Source node.
123    \param _t Target node.
124    */
125    MinCostFlow(Graph& _g, LengthMap& _length, CapacityMap& _cap,
126                Node _s, Node _t) :
127      g(_g), length(_length), capacity(_cap), flow(_g), potential(_g),
128      s(_s), t(_t),
129      res_graph(g, capacity, flow),
130      mod_length(res_graph, length, potential),
131      dijkstra(res_graph, mod_length) {
132      reset();
133      }
134
135    /*! Tries to augment the flow between s and t by 1.
136      The return value shows if the augmentation is successful.
137     */
138    bool augment() {
139      dijkstra.run(s);
140      if (!dijkstra.reached(t)) {
141
142        //Unsuccessful augmentation.
143        return false;
144      } else {
145
146        //We have to change the potential
147        for(typename ResGW::NodeIt n(res_graph); n!=INVALID; ++n)
148          potential.set(n, potential[n]+dijkstra.distMap()[n]);
149
150        //Augmenting on the shortest path
151        Node n=t;
152        ResGraphEdge e;
153        while (n!=s){
154          e = dijkstra.pred(n);
155          n = dijkstra.predNode(n);
156          res_graph.augment(e,1);
157          //Let's update the total length
158          if (res_graph.forward(e))
159            total_length += length[e];
160          else
161            total_length -= length[e];
162        }
163
164        return true;
165      }
166    }
167
168    /*! \brief Runs the algorithm.
169
170    Runs the algorithm.
171    Returns k if there is a flow of value at least k from s to t.
172    Otherwise it returns the maximum value of a flow from s to t.
173
174    \param k The value of the flow we are looking for.
175
176    \todo May be it does make sense to be able to start with a nonzero
177    feasible primal-dual solution pair as well.
178
179    \todo If the actual flow value is bigger than k, then everything is
180    cleared and the algorithm starts from zero flow. Is it a good approach?
181    */
182    int run(int k) {
183      if (flowValue()>k) reset();
184      while (flowValue()<k && augment()) { }
185      return flowValue();
186    }
187
188    /*! \brief The class is reset to zero flow and potential.
189      The class is reset to zero flow and potential.
190     */
191    void reset() {
192      total_length=0;
193      for (typename Graph::EdgeIt e(g); e!=INVALID; ++e) flow.set(e, 0);
194      for (typename Graph::NodeIt n(g); n!=INVALID; ++n) potential.set(n, 0);
195    }
196
197    /*! Returns the value of the actual flow.
198     */
199    int flowValue() const {
200      int i=0;
201      for (typename Graph::OutEdgeIt e(g, s); e!=INVALID; ++e) i+=flow[e];
202      for (typename Graph::InEdgeIt e(g, s); e!=INVALID; ++e) i-=flow[e];
203      return i;
204    }
205
206    /// Total cost of the found flow.
207
208    /// This function gives back the total cost of the found flow.
209    Length totalLength(){
211    }
212
213    ///Returns a const reference to the EdgeMap \c flow.
214
215    ///Returns a const reference to the EdgeMap \c flow.
216    const EdgeIntMap &getFlow() const { return flow;}
217
218    /*! \brief Returns a const reference to the NodeMap \c potential (the dual solution).
219
220    Returns a const reference to the NodeMap \c potential (the dual solution).
221    */
222    const PotentialMap &getPotential() const { return potential;}
223
224    /*! \brief Checking the complementary slackness optimality criteria.
225
226    This function checks, whether the given flow and potential
227    satisfy the complementary slackness conditions (i.e. these are optimal).
228    This function only checks optimality, doesn't bother with feasibility.
229    For testing purpose.
230    */
231    bool checkComplementarySlackness(){
232      Length mod_pot;
233      Length fl_e;
234        for(typename Graph::EdgeIt e(g); e!=INVALID; ++e) {
235        //C^{\Pi}_{i,j}
236        mod_pot = length[e]-potential[g.target(e)]+potential[g.source(e)];
237        fl_e = flow[e];
238        if (0<fl_e && fl_e<capacity[e]) {
239          /// \todo better comparison is needed for real types, moreover,
240          /// this comparison here is superfluous.
241          if (mod_pot != 0)
242            return false;
243        }
244        else {
245          if (mod_pot > 0 && fl_e != 0)
246            return false;
247          if (mod_pot < 0 && fl_e != capacity[e])
248            return false;
249        }
250      }
251      return true;
252    }
253
254  }; //class MinCostFlow
255
256  ///@}
257
258} //namespace lemon
259
260#endif //LEMON_MIN_COST_FLOW_H
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