0
5
0
... | ... |
@@ -41,97 +41,98 @@ |
41 | 41 |
/// By default it is the same as \c V. |
42 | 42 |
template <typename GR, typename V = int, typename C = V> |
43 | 43 |
struct CapacityScalingDefaultTraits |
44 | 44 |
{ |
45 | 45 |
/// The type of the digraph |
46 | 46 |
typedef GR Digraph; |
47 | 47 |
/// The type of the flow amounts, capacity bounds and supply values |
48 | 48 |
typedef V Value; |
49 | 49 |
/// The type of the arc costs |
50 | 50 |
typedef C Cost; |
51 | 51 |
|
52 | 52 |
/// \brief The type of the heap used for internal Dijkstra computations. |
53 | 53 |
/// |
54 | 54 |
/// The type of the heap used for internal Dijkstra computations. |
55 | 55 |
/// It must conform to the \ref lemon::concepts::Heap "Heap" concept, |
56 | 56 |
/// its priority type must be \c Cost and its cross reference type |
57 | 57 |
/// must be \ref RangeMap "RangeMap<int>". |
58 | 58 |
typedef BinHeap<Cost, RangeMap<int> > Heap; |
59 | 59 |
}; |
60 | 60 |
|
61 | 61 |
/// \addtogroup min_cost_flow_algs |
62 | 62 |
/// @{ |
63 | 63 |
|
64 | 64 |
/// \brief Implementation of the Capacity Scaling algorithm for |
65 | 65 |
/// finding a \ref min_cost_flow "minimum cost flow". |
66 | 66 |
/// |
67 | 67 |
/// \ref CapacityScaling implements the capacity scaling version |
68 | 68 |
/// of the successive shortest path algorithm for finding a |
69 | 69 |
/// \ref min_cost_flow "minimum cost flow" \ref amo93networkflows, |
70 | 70 |
/// \ref edmondskarp72theoretical. It is an efficient dual |
71 | 71 |
/// solution method. |
72 | 72 |
/// |
73 | 73 |
/// Most of the parameters of the problem (except for the digraph) |
74 | 74 |
/// can be given using separate functions, and the algorithm can be |
75 | 75 |
/// executed using the \ref run() function. If some parameters are not |
76 | 76 |
/// specified, then default values will be used. |
77 | 77 |
/// |
78 | 78 |
/// \tparam GR The digraph type the algorithm runs on. |
79 | 79 |
/// \tparam V The number type used for flow amounts, capacity bounds |
80 | 80 |
/// and supply values in the algorithm. By default, it is \c int. |
81 | 81 |
/// \tparam C The number type used for costs and potentials in the |
82 | 82 |
/// algorithm. By default, it is the same as \c V. |
83 | 83 |
/// \tparam TR The traits class that defines various types used by the |
84 | 84 |
/// algorithm. By default, it is \ref CapacityScalingDefaultTraits |
85 | 85 |
/// "CapacityScalingDefaultTraits<GR, V, C>". |
86 | 86 |
/// In most cases, this parameter should not be set directly, |
87 | 87 |
/// consider to use the named template parameters instead. |
88 | 88 |
/// |
89 |
/// \warning Both |
|
89 |
/// \warning Both \c V and \c C must be signed number types. |
|
90 |
/// \warning All input data (capacities, supply values, and costs) must |
|
90 | 91 |
/// be integer. |
91 | 92 |
/// \warning This algorithm does not support negative costs for such |
92 | 93 |
/// arcs that have infinite upper bound. |
93 | 94 |
#ifdef DOXYGEN |
94 | 95 |
template <typename GR, typename V, typename C, typename TR> |
95 | 96 |
#else |
96 | 97 |
template < typename GR, typename V = int, typename C = V, |
97 | 98 |
typename TR = CapacityScalingDefaultTraits<GR, V, C> > |
98 | 99 |
#endif |
99 | 100 |
class CapacityScaling |
100 | 101 |
{ |
101 | 102 |
public: |
102 | 103 |
|
103 | 104 |
/// The type of the digraph |
104 | 105 |
typedef typename TR::Digraph Digraph; |
105 | 106 |
/// The type of the flow amounts, capacity bounds and supply values |
106 | 107 |
typedef typename TR::Value Value; |
107 | 108 |
/// The type of the arc costs |
108 | 109 |
typedef typename TR::Cost Cost; |
109 | 110 |
|
110 | 111 |
/// The type of the heap used for internal Dijkstra computations |
111 | 112 |
typedef typename TR::Heap Heap; |
112 | 113 |
|
113 | 114 |
/// The \ref CapacityScalingDefaultTraits "traits class" of the algorithm |
114 | 115 |
typedef TR Traits; |
115 | 116 |
|
116 | 117 |
public: |
117 | 118 |
|
118 | 119 |
/// \brief Problem type constants for the \c run() function. |
119 | 120 |
/// |
120 | 121 |
/// Enum type containing the problem type constants that can be |
121 | 122 |
/// returned by the \ref run() function of the algorithm. |
122 | 123 |
enum ProblemType { |
123 | 124 |
/// The problem has no feasible solution (flow). |
124 | 125 |
INFEASIBLE, |
125 | 126 |
/// The problem has optimal solution (i.e. it is feasible and |
126 | 127 |
/// bounded), and the algorithm has found optimal flow and node |
127 | 128 |
/// potentials (primal and dual solutions). |
128 | 129 |
OPTIMAL, |
129 | 130 |
/// The digraph contains an arc of negative cost and infinite |
130 | 131 |
/// upper bound. It means that the objective function is unbounded |
131 | 132 |
/// on that arc, however, note that it could actually be bounded |
132 | 133 |
/// over the feasible flows, but this algroithm cannot handle |
133 | 134 |
/// these cases. |
134 | 135 |
UNBOUNDED |
135 | 136 |
}; |
136 | 137 |
|
137 | 138 |
private: |
... | ... |
@@ -68,97 +68,98 @@ |
68 | 68 |
typedef double LargeCost; |
69 | 69 |
}; |
70 | 70 |
|
71 | 71 |
// Default traits class for integer cost types |
72 | 72 |
template <typename GR, typename V, typename C> |
73 | 73 |
struct CostScalingDefaultTraits<GR, V, C, true> |
74 | 74 |
{ |
75 | 75 |
typedef GR Digraph; |
76 | 76 |
typedef V Value; |
77 | 77 |
typedef C Cost; |
78 | 78 |
#ifdef LEMON_HAVE_LONG_LONG |
79 | 79 |
typedef long long LargeCost; |
80 | 80 |
#else |
81 | 81 |
typedef long LargeCost; |
82 | 82 |
#endif |
83 | 83 |
}; |
84 | 84 |
|
85 | 85 |
|
86 | 86 |
/// \addtogroup min_cost_flow_algs |
87 | 87 |
/// @{ |
88 | 88 |
|
89 | 89 |
/// \brief Implementation of the Cost Scaling algorithm for |
90 | 90 |
/// finding a \ref min_cost_flow "minimum cost flow". |
91 | 91 |
/// |
92 | 92 |
/// \ref CostScaling implements a cost scaling algorithm that performs |
93 | 93 |
/// push/augment and relabel operations for finding a \ref min_cost_flow |
94 | 94 |
/// "minimum cost flow" \ref amo93networkflows, \ref goldberg90approximation, |
95 | 95 |
/// \ref goldberg97efficient, \ref bunnagel98efficient. |
96 | 96 |
/// It is a highly efficient primal-dual solution method, which |
97 | 97 |
/// can be viewed as the generalization of the \ref Preflow |
98 | 98 |
/// "preflow push-relabel" algorithm for the maximum flow problem. |
99 | 99 |
/// |
100 | 100 |
/// Most of the parameters of the problem (except for the digraph) |
101 | 101 |
/// can be given using separate functions, and the algorithm can be |
102 | 102 |
/// executed using the \ref run() function. If some parameters are not |
103 | 103 |
/// specified, then default values will be used. |
104 | 104 |
/// |
105 | 105 |
/// \tparam GR The digraph type the algorithm runs on. |
106 | 106 |
/// \tparam V The number type used for flow amounts, capacity bounds |
107 | 107 |
/// and supply values in the algorithm. By default, it is \c int. |
108 | 108 |
/// \tparam C The number type used for costs and potentials in the |
109 | 109 |
/// algorithm. By default, it is the same as \c V. |
110 | 110 |
/// \tparam TR The traits class that defines various types used by the |
111 | 111 |
/// algorithm. By default, it is \ref CostScalingDefaultTraits |
112 | 112 |
/// "CostScalingDefaultTraits<GR, V, C>". |
113 | 113 |
/// In most cases, this parameter should not be set directly, |
114 | 114 |
/// consider to use the named template parameters instead. |
115 | 115 |
/// |
116 |
/// \warning Both |
|
116 |
/// \warning Both \c V and \c C must be signed number types. |
|
117 |
/// \warning All input data (capacities, supply values, and costs) must |
|
117 | 118 |
/// be integer. |
118 | 119 |
/// \warning This algorithm does not support negative costs for such |
119 | 120 |
/// arcs that have infinite upper bound. |
120 | 121 |
/// |
121 | 122 |
/// \note %CostScaling provides three different internal methods, |
122 | 123 |
/// from which the most efficient one is used by default. |
123 | 124 |
/// For more information, see \ref Method. |
124 | 125 |
#ifdef DOXYGEN |
125 | 126 |
template <typename GR, typename V, typename C, typename TR> |
126 | 127 |
#else |
127 | 128 |
template < typename GR, typename V = int, typename C = V, |
128 | 129 |
typename TR = CostScalingDefaultTraits<GR, V, C> > |
129 | 130 |
#endif |
130 | 131 |
class CostScaling |
131 | 132 |
{ |
132 | 133 |
public: |
133 | 134 |
|
134 | 135 |
/// The type of the digraph |
135 | 136 |
typedef typename TR::Digraph Digraph; |
136 | 137 |
/// The type of the flow amounts, capacity bounds and supply values |
137 | 138 |
typedef typename TR::Value Value; |
138 | 139 |
/// The type of the arc costs |
139 | 140 |
typedef typename TR::Cost Cost; |
140 | 141 |
|
141 | 142 |
/// \brief The large cost type |
142 | 143 |
/// |
143 | 144 |
/// The large cost type used for internal computations. |
144 | 145 |
/// By default, it is \c long \c long if the \c Cost type is integer, |
145 | 146 |
/// otherwise it is \c double. |
146 | 147 |
typedef typename TR::LargeCost LargeCost; |
147 | 148 |
|
148 | 149 |
/// The \ref CostScalingDefaultTraits "traits class" of the algorithm |
149 | 150 |
typedef TR Traits; |
150 | 151 |
|
151 | 152 |
public: |
152 | 153 |
|
153 | 154 |
/// \brief Problem type constants for the \c run() function. |
154 | 155 |
/// |
155 | 156 |
/// Enum type containing the problem type constants that can be |
156 | 157 |
/// returned by the \ref run() function of the algorithm. |
157 | 158 |
enum ProblemType { |
158 | 159 |
/// The problem has no feasible solution (flow). |
159 | 160 |
INFEASIBLE, |
160 | 161 |
/// The problem has optimal solution (i.e. it is feasible and |
161 | 162 |
/// bounded), and the algorithm has found optimal flow and node |
162 | 163 |
/// potentials (primal and dual solutions). |
163 | 164 |
OPTIMAL, |
164 | 165 |
/// The digraph contains an arc of negative cost and infinite |
... | ... |
@@ -20,97 +20,98 @@ |
20 | 20 |
#define LEMON_CYCLE_CANCELING_H |
21 | 21 |
|
22 | 22 |
/// \ingroup min_cost_flow_algs |
23 | 23 |
/// \file |
24 | 24 |
/// \brief Cycle-canceling algorithms for finding a minimum cost flow. |
25 | 25 |
|
26 | 26 |
#include <vector> |
27 | 27 |
#include <limits> |
28 | 28 |
|
29 | 29 |
#include <lemon/core.h> |
30 | 30 |
#include <lemon/maps.h> |
31 | 31 |
#include <lemon/path.h> |
32 | 32 |
#include <lemon/math.h> |
33 | 33 |
#include <lemon/static_graph.h> |
34 | 34 |
#include <lemon/adaptors.h> |
35 | 35 |
#include <lemon/circulation.h> |
36 | 36 |
#include <lemon/bellman_ford.h> |
37 | 37 |
#include <lemon/howard_mmc.h> |
38 | 38 |
|
39 | 39 |
namespace lemon { |
40 | 40 |
|
41 | 41 |
/// \addtogroup min_cost_flow_algs |
42 | 42 |
/// @{ |
43 | 43 |
|
44 | 44 |
/// \brief Implementation of cycle-canceling algorithms for |
45 | 45 |
/// finding a \ref min_cost_flow "minimum cost flow". |
46 | 46 |
/// |
47 | 47 |
/// \ref CycleCanceling implements three different cycle-canceling |
48 | 48 |
/// algorithms for finding a \ref min_cost_flow "minimum cost flow" |
49 | 49 |
/// \ref amo93networkflows, \ref klein67primal, |
50 | 50 |
/// \ref goldberg89cyclecanceling. |
51 | 51 |
/// The most efficent one (both theoretically and practically) |
52 | 52 |
/// is the \ref CANCEL_AND_TIGHTEN "Cancel and Tighten" algorithm, |
53 | 53 |
/// thus it is the default method. |
54 | 54 |
/// It is strongly polynomial, but in practice, it is typically much |
55 | 55 |
/// slower than the scaling algorithms and NetworkSimplex. |
56 | 56 |
/// |
57 | 57 |
/// Most of the parameters of the problem (except for the digraph) |
58 | 58 |
/// can be given using separate functions, and the algorithm can be |
59 | 59 |
/// executed using the \ref run() function. If some parameters are not |
60 | 60 |
/// specified, then default values will be used. |
61 | 61 |
/// |
62 | 62 |
/// \tparam GR The digraph type the algorithm runs on. |
63 | 63 |
/// \tparam V The number type used for flow amounts, capacity bounds |
64 | 64 |
/// and supply values in the algorithm. By default, it is \c int. |
65 | 65 |
/// \tparam C The number type used for costs and potentials in the |
66 | 66 |
/// algorithm. By default, it is the same as \c V. |
67 | 67 |
/// |
68 |
/// \warning Both |
|
68 |
/// \warning Both \c V and \c C must be signed number types. |
|
69 |
/// \warning All input data (capacities, supply values, and costs) must |
|
69 | 70 |
/// be integer. |
70 | 71 |
/// \warning This algorithm does not support negative costs for such |
71 | 72 |
/// arcs that have infinite upper bound. |
72 | 73 |
/// |
73 | 74 |
/// \note For more information about the three available methods, |
74 | 75 |
/// see \ref Method. |
75 | 76 |
#ifdef DOXYGEN |
76 | 77 |
template <typename GR, typename V, typename C> |
77 | 78 |
#else |
78 | 79 |
template <typename GR, typename V = int, typename C = V> |
79 | 80 |
#endif |
80 | 81 |
class CycleCanceling |
81 | 82 |
{ |
82 | 83 |
public: |
83 | 84 |
|
84 | 85 |
/// The type of the digraph |
85 | 86 |
typedef GR Digraph; |
86 | 87 |
/// The type of the flow amounts, capacity bounds and supply values |
87 | 88 |
typedef V Value; |
88 | 89 |
/// The type of the arc costs |
89 | 90 |
typedef C Cost; |
90 | 91 |
|
91 | 92 |
public: |
92 | 93 |
|
93 | 94 |
/// \brief Problem type constants for the \c run() function. |
94 | 95 |
/// |
95 | 96 |
/// Enum type containing the problem type constants that can be |
96 | 97 |
/// returned by the \ref run() function of the algorithm. |
97 | 98 |
enum ProblemType { |
98 | 99 |
/// The problem has no feasible solution (flow). |
99 | 100 |
INFEASIBLE, |
100 | 101 |
/// The problem has optimal solution (i.e. it is feasible and |
101 | 102 |
/// bounded), and the algorithm has found optimal flow and node |
102 | 103 |
/// potentials (primal and dual solutions). |
103 | 104 |
OPTIMAL, |
104 | 105 |
/// The digraph contains an arc of negative cost and infinite |
105 | 106 |
/// upper bound. It means that the objective function is unbounded |
106 | 107 |
/// on that arc, however, note that it could actually be bounded |
107 | 108 |
/// over the feasible flows, but this algroithm cannot handle |
108 | 109 |
/// these cases. |
109 | 110 |
UNBOUNDED |
110 | 111 |
}; |
111 | 112 |
|
112 | 113 |
/// \brief Constants for selecting the used method. |
113 | 114 |
/// |
114 | 115 |
/// Enum type containing constants for selecting the used method |
115 | 116 |
/// for the \ref run() function. |
116 | 117 |
/// |
1 | 1 |
/* -*- mode: C++; indent-tabs-mode: nil; -*- |
2 | 2 |
* |
3 | 3 |
* This file is a part of LEMON, a generic C++ optimization library. |
4 | 4 |
* |
5 | 5 |
* Copyright (C) 2003-2009 |
6 | 6 |
* Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport |
7 | 7 |
* (Egervary Research Group on Combinatorial Optimization, EGRES). |
8 | 8 |
* |
9 | 9 |
* Permission to use, modify and distribute this software is granted |
10 | 10 |
* provided that this copyright notice appears in all copies. For |
11 | 11 |
* precise terms see the accompanying LICENSE file. |
12 | 12 |
* |
13 | 13 |
* This software is provided "AS IS" with no warranty of any kind, |
14 | 14 |
* express or implied, and with no claim as to its suitability for any |
15 | 15 |
* purpose. |
16 | 16 |
* |
17 | 17 |
*/ |
18 | 18 |
|
19 | 19 |
#ifndef LEMON_KRUSKAL_H |
20 | 20 |
#define LEMON_KRUSKAL_H |
21 | 21 |
|
22 | 22 |
#include <algorithm> |
23 | 23 |
#include <vector> |
24 | 24 |
#include <lemon/unionfind.h> |
25 | 25 |
#include <lemon/maps.h> |
26 | 26 |
|
27 | 27 |
#include <lemon/core.h> |
28 | 28 |
#include <lemon/bits/traits.h> |
29 | 29 |
|
30 | 30 |
///\ingroup spantree |
31 | 31 |
///\file |
32 | 32 |
///\brief Kruskal's algorithm to compute a minimum cost spanning tree |
33 |
/// |
|
34 |
///Kruskal's algorithm to compute a minimum cost spanning tree. |
|
35 |
/// |
|
36 | 33 |
|
37 | 34 |
namespace lemon { |
38 | 35 |
|
39 | 36 |
namespace _kruskal_bits { |
40 | 37 |
|
41 | 38 |
// Kruskal for directed graphs. |
42 | 39 |
|
43 | 40 |
template <typename Digraph, typename In, typename Out> |
44 | 41 |
typename disable_if<lemon::UndirectedTagIndicator<Digraph>, |
45 | 42 |
typename In::value_type::second_type >::type |
46 | 43 |
kruskal(const Digraph& digraph, const In& in, Out& out,dummy<0> = 0) { |
47 | 44 |
typedef typename In::value_type::second_type Value; |
48 | 45 |
typedef typename Digraph::template NodeMap<int> IndexMap; |
49 | 46 |
typedef typename Digraph::Node Node; |
50 | 47 |
|
51 | 48 |
IndexMap index(digraph); |
52 | 49 |
UnionFind<IndexMap> uf(index); |
53 | 50 |
for (typename Digraph::NodeIt it(digraph); it != INVALID; ++it) { |
54 | 51 |
uf.insert(it); |
55 | 52 |
} |
56 | 53 |
|
57 | 54 |
Value tree_value = 0; |
58 | 55 |
for (typename In::const_iterator it = in.begin(); it != in.end(); ++it) { |
59 | 56 |
if (uf.join(digraph.target(it->first),digraph.source(it->first))) { |
60 | 57 |
out.set(it->first, true); |
61 | 58 |
tree_value += it->second; |
62 | 59 |
} |
63 | 60 |
else { |
64 | 61 |
out.set(it->first, false); |
65 | 62 |
} |
66 | 63 |
} |
67 | 64 |
return tree_value; |
68 | 65 |
} |
69 | 66 |
|
70 | 67 |
// Kruskal for undirected graphs. |
71 | 68 |
|
72 | 69 |
template <typename Graph, typename In, typename Out> |
73 | 70 |
typename enable_if<lemon::UndirectedTagIndicator<Graph>, |
74 | 71 |
typename In::value_type::second_type >::type |
75 | 72 |
kruskal(const Graph& graph, const In& in, Out& out,dummy<1> = 1) { |
76 | 73 |
typedef typename In::value_type::second_type Value; |
77 | 74 |
typedef typename Graph::template NodeMap<int> IndexMap; |
78 | 75 |
typedef typename Graph::Node Node; |
79 | 76 |
|
80 | 77 |
IndexMap index(graph); |
81 | 78 |
UnionFind<IndexMap> uf(index); |
82 | 79 |
for (typename Graph::NodeIt it(graph); it != INVALID; ++it) { |
83 | 80 |
uf.insert(it); |
... | ... |
@@ -18,97 +18,98 @@ |
18 | 18 |
|
19 | 19 |
#ifndef LEMON_NETWORK_SIMPLEX_H |
20 | 20 |
#define LEMON_NETWORK_SIMPLEX_H |
21 | 21 |
|
22 | 22 |
/// \ingroup min_cost_flow_algs |
23 | 23 |
/// |
24 | 24 |
/// \file |
25 | 25 |
/// \brief Network Simplex algorithm for finding a minimum cost flow. |
26 | 26 |
|
27 | 27 |
#include <vector> |
28 | 28 |
#include <limits> |
29 | 29 |
#include <algorithm> |
30 | 30 |
|
31 | 31 |
#include <lemon/core.h> |
32 | 32 |
#include <lemon/math.h> |
33 | 33 |
|
34 | 34 |
namespace lemon { |
35 | 35 |
|
36 | 36 |
/// \addtogroup min_cost_flow_algs |
37 | 37 |
/// @{ |
38 | 38 |
|
39 | 39 |
/// \brief Implementation of the primal Network Simplex algorithm |
40 | 40 |
/// for finding a \ref min_cost_flow "minimum cost flow". |
41 | 41 |
/// |
42 | 42 |
/// \ref NetworkSimplex implements the primal Network Simplex algorithm |
43 | 43 |
/// for finding a \ref min_cost_flow "minimum cost flow" |
44 | 44 |
/// \ref amo93networkflows, \ref dantzig63linearprog, |
45 | 45 |
/// \ref kellyoneill91netsimplex. |
46 | 46 |
/// This algorithm is a highly efficient specialized version of the |
47 | 47 |
/// linear programming simplex method directly for the minimum cost |
48 | 48 |
/// flow problem. |
49 | 49 |
/// |
50 | 50 |
/// In general, %NetworkSimplex is the fastest implementation available |
51 | 51 |
/// in LEMON for this problem. |
52 | 52 |
/// Moreover, it supports both directions of the supply/demand inequality |
53 | 53 |
/// constraints. For more information, see \ref SupplyType. |
54 | 54 |
/// |
55 | 55 |
/// Most of the parameters of the problem (except for the digraph) |
56 | 56 |
/// can be given using separate functions, and the algorithm can be |
57 | 57 |
/// executed using the \ref run() function. If some parameters are not |
58 | 58 |
/// specified, then default values will be used. |
59 | 59 |
/// |
60 | 60 |
/// \tparam GR The digraph type the algorithm runs on. |
61 | 61 |
/// \tparam V The number type used for flow amounts, capacity bounds |
62 | 62 |
/// and supply values in the algorithm. By default, it is \c int. |
63 | 63 |
/// \tparam C The number type used for costs and potentials in the |
64 | 64 |
/// algorithm. By default, it is the same as \c V. |
65 | 65 |
/// |
66 |
/// \warning Both |
|
66 |
/// \warning Both \c V and \c C must be signed number types. |
|
67 |
/// \warning All input data (capacities, supply values, and costs) must |
|
67 | 68 |
/// be integer. |
68 | 69 |
/// |
69 | 70 |
/// \note %NetworkSimplex provides five different pivot rule |
70 | 71 |
/// implementations, from which the most efficient one is used |
71 | 72 |
/// by default. For more information, see \ref PivotRule. |
72 | 73 |
template <typename GR, typename V = int, typename C = V> |
73 | 74 |
class NetworkSimplex |
74 | 75 |
{ |
75 | 76 |
public: |
76 | 77 |
|
77 | 78 |
/// The type of the flow amounts, capacity bounds and supply values |
78 | 79 |
typedef V Value; |
79 | 80 |
/// The type of the arc costs |
80 | 81 |
typedef C Cost; |
81 | 82 |
|
82 | 83 |
public: |
83 | 84 |
|
84 | 85 |
/// \brief Problem type constants for the \c run() function. |
85 | 86 |
/// |
86 | 87 |
/// Enum type containing the problem type constants that can be |
87 | 88 |
/// returned by the \ref run() function of the algorithm. |
88 | 89 |
enum ProblemType { |
89 | 90 |
/// The problem has no feasible solution (flow). |
90 | 91 |
INFEASIBLE, |
91 | 92 |
/// The problem has optimal solution (i.e. it is feasible and |
92 | 93 |
/// bounded), and the algorithm has found optimal flow and node |
93 | 94 |
/// potentials (primal and dual solutions). |
94 | 95 |
OPTIMAL, |
95 | 96 |
/// The objective function of the problem is unbounded, i.e. |
96 | 97 |
/// there is a directed cycle having negative total cost and |
97 | 98 |
/// infinite upper bound. |
98 | 99 |
UNBOUNDED |
99 | 100 |
}; |
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|
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/// \brief Constants for selecting the type of the supply constraints. |
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/// |
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/// Enum type containing constants for selecting the supply type, |
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/// i.e. the direction of the inequalities in the supply/demand |
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/// constraints of the \ref min_cost_flow "minimum cost flow problem". |
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/// |
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/// The default supply type is \c GEQ, the \c LEQ type can be |
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/// selected using \ref supplyType(). |
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/// The equality form is a special case of both supply types. |
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enum SupplyType { |
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/// This option means that there are <em>"greater or equal"</em> |
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/// supply/demand constraints in the definition of the problem. |
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GEQ, |
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/// This option means that there are <em>"less or equal"</em> |
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