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\subsection pri-loc-var Private member variables |
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Private member variables should start with underscore |
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Private member variables should start with underscore. |
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\code |
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|
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_start_with_underscore |
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\endcode |
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|
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\subsection cs-excep Exceptions |
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@@ -406,10 +406,10 @@ |
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- \ref CycleCanceling Cycle-Canceling algorithms, two of which are |
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strongly polynomial \ref klein67primal, \ref goldberg89cyclecanceling. |
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In general NetworkSimplex is the most efficient implementation, |
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but in special cases other algorithms could be faster. |
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In general, \ref NetworkSimplex and \ref CostScaling are the most efficient |
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implementations, but the other two algorithms could be faster in special cases. |
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For example, if the total supply and/or capacities are rather small, |
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CapacityScaling is usually the fastest algorithm (without effective scaling). |
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\ref CapacityScaling is usually the fastest algorithm (without effective scaling). |
|
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*/ |
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|
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/** |
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- \ref HowardMmc Howard's policy iteration algorithm |
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\ref dasdan98minmeancycle. |
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In practice, the \ref HowardMmc "Howard" algorithm |
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In practice, the \ref HowardMmc "Howard" algorithm turned out to be by far the |
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most efficient one, though the best known theoretical bound on its running |
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time is exponential. |
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Both \ref KarpMmc "Karp" and \ref HartmannOrlinMmc "Hartmann-Orlin" algorithms |
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*/ |
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/** |
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@defgroup planar |
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@defgroup planar Planar Embedding and Drawing |
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@ingroup algs |
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\brief Algorithms for planarity checking, embedding and drawing |
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/// |
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/// \warning Both number types must be signed and all input data must |
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/// be integer. |
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/// \warning This algorithm does not support negative costs for such |
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/// arcs that have infinite upper bound. |
|
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/// \warning This algorithm does not support negative costs for |
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/// arcs having infinite upper bound. |
|
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#ifdef DOXYGEN |
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template <typename GR, typename V, typename C, typename TR> |
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#else |
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/// calling \ref run(), the supply of each node will be set to zero. |
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/// |
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/// Using this function has the same effect as using \ref supplyMap() |
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/// with |
|
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/// with a map in which \c k is assigned to \c s, \c -k is |
|
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/// assigned to \c t and all other nodes have zero supply value. |
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/// |
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/// \param s The source node. |
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@@ -97,6 +97,9 @@ |
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/// can be viewed as the generalization of the \ref Preflow |
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/// "preflow push-relabel" algorithm for the maximum flow problem. |
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/// |
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/// In general, \ref NetworkSimplex and \ref CostScaling are the fastest |
|
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/// implementations available in LEMON for this problem. |
|
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/// |
|
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/// Most of the parameters of the problem (except for the digraph) |
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/// can be given using separate functions, and the algorithm can be |
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/// executed using the \ref run() function. If some parameters are not |
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@@ -115,8 +118,8 @@ |
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/// |
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/// \warning Both number types must be signed and all input data must |
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/// be integer. |
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/// \warning This algorithm does not support negative costs for such |
|
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/// arcs that have infinite upper bound. |
|
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/// \warning This algorithm does not support negative costs for |
|
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/// arcs having infinite upper bound. |
|
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/// |
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/// \note %CostScaling provides three different internal methods, |
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/// from which the most efficient one is used by default. |
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@@ -178,7 +181,7 @@ |
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/// in their base operations, which are used in conjunction with the |
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/// relabel operation. |
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/// By default, the so called \ref PARTIAL_AUGMENT |
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/// "Partial Augment-Relabel" method is used, which |
|
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/// "Partial Augment-Relabel" method is used, which turned out to be |
|
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/// the most efficient and the most robust on various test inputs. |
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/// However, the other methods can be selected using the \ref run() |
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/// function with the proper parameter. |
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@@ -447,7 +450,7 @@ |
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/// calling \ref run(), the supply of each node will be set to zero. |
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/// |
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/// Using this function has the same effect as using \ref supplyMap() |
450 |
/// with |
|
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/// with a map in which \c k is assigned to \c s, \c -k is |
|
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/// assigned to \c t and all other nodes have zero supply value. |
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/// |
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/// \param s The source node. |
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@@ -67,8 +67,8 @@ |
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/// |
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/// \warning Both number types must be signed and all input data must |
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/// be integer. |
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/// \warning This algorithm does not support negative costs for such |
|
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/// arcs that have infinite upper bound. |
|
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/// \warning This algorithm does not support negative costs for |
|
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/// arcs having infinite upper bound. |
|
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/// |
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/// \note For more information about the three available methods, |
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/// see \ref Method. |
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@@ -116,8 +116,7 @@ |
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/// |
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/// \ref CycleCanceling provides three different cycle-canceling |
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/// methods. By default, \ref CANCEL_AND_TIGHTEN "Cancel and Tighten" |
119 |
/// is used, which proved to be the most efficient and the most robust |
|
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/// on various test inputs. |
|
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/// is used, which is by far the most efficient and the most robust. |
|
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/// However, the other methods can be selected using the \ref run() |
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/// function with the proper parameter. |
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enum Method { |
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@@ -349,7 +348,7 @@ |
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/// calling \ref run(), the supply of each node will be set to zero. |
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/// |
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/// Using this function has the same effect as using \ref supplyMap() |
352 |
/// with |
|
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/// with a map in which \c k is assigned to \c s, \c -k is |
|
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/// assigned to \c t and all other nodes have zero supply value. |
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/// |
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/// \param s The source node. |
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@@ -36,7 +36,7 @@ |
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|
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///Euler tour iterator for digraphs. |
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|
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/// \ingroup |
|
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/// \ingroup graph_properties |
|
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///This iterator provides an Euler tour (Eulerian circuit) of a \e directed |
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///graph (if there exists) and it converts to the \c Arc type of the digraph. |
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/// |
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@@ -47,10 +47,10 @@ |
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/// linear programming simplex method directly for the minimum cost |
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/// flow problem. |
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/// |
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/// In general, %NetworkSimplex is the fastest implementation available |
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/// in LEMON for this problem. |
|
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/// Moreover, it supports both directions of the supply/demand inequality |
|
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/// constraints. For more information, see \ref SupplyType. |
|
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/// In general, \ref NetworkSimplex and \ref CostScaling are the fastest |
|
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/// implementations available in LEMON for this problem. |
|
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/// Furthermore, this class supports both directions of the supply/demand |
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/// inequality constraints. For more information, see \ref SupplyType. |
|
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/// |
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/// Most of the parameters of the problem (except for the digraph) |
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/// can be given using separate functions, and the algorithm can be |
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@@ -125,7 +125,7 @@ |
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/// implementations that significantly affect the running time |
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/// of the algorithm. |
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/// By default, \ref BLOCK_SEARCH "Block Search" is used, which |
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/// |
|
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/// turend out to be the most efficient and the most robust on various |
|
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/// test inputs. |
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/// However, another pivot rule can be selected using the \ref run() |
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/// function with the proper parameter. |
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@@ -734,6 +734,8 @@ |
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/// of the algorithm. |
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/// |
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/// \return <tt>(*this)</tt> |
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/// |
|
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/// \sa supplyType() |
|
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template<typename SupplyMap> |
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NetworkSimplex& supplyMap(const SupplyMap& map) { |
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for (NodeIt n(_graph); n != INVALID; ++n) { |
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@@ -750,7 +752,7 @@ |
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/// calling \ref run(), the supply of each node will be set to zero. |
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/// |
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/// Using this function has the same effect as using \ref supplyMap() |
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/// with |
|
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/// with a map in which \c k is assigned to \c s, \c -k is |
|
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/// assigned to \c t and all other nodes have zero supply value. |
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/// |
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/// \param s The source node. |
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