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kpeter (Peter Kovacs)
kpeter@inf.elte.hu
Small doc fixes and improvements (#359)
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4 files changed with 22 insertions and 23 deletions:
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LEMON code without an explicit copyright notice is covered by the following
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copyright/license.
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Copyright (C) 2003-2009 Egervary Jeno Kombinatorikus Optimalizalasi
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Copyright (C) 2003-2010 Egervary Jeno Kombinatorikus Optimalizalasi
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Kutatocsoport (Egervary Combinatorial Optimization Research Group,
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EGRES).
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===========================================================================
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Boost Software License, Version 1.0
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===========================================================================
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Permission is hereby granted, free of charge, to any person or organization
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obtaining a copy of the software and accompanying documentation covered by
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this license (the "Software") to use, reproduce, display, distribute,
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execute, and transmit the Software, and to prepare derivative works of the
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Software, and to permit third-parties to whom the Software is furnished to
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do so, all subject to the following:
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The copyright notices in the Software and this entire statement, including
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the above license grant, this restriction and the following disclaimer,
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must be included in all copies of the Software, in whole or in part, and
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all derivative works of the Software, unless such copies or derivative
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works are solely in the form of machine-executable object code generated by
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a source language processor.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE, TITLE AND NON-INFRINGEMENT. IN NO EVENT
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SHALL THE COPYRIGHT HOLDERS OR ANYONE DISTRIBUTING THE SOFTWARE BE LIABLE
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FOR ANY DAMAGES OR OTHER LIABILITY, WHETHER IN CONTRACT, TORT OR OTHERWISE,
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ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
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DEALINGS IN THE SOFTWARE.
Ignore white space 6 line context
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@@ -218,104 +218,96 @@
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  Dijkstra<Digraph, TimeMap> dijkstra(graph, time);
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  dijkstra.run(source, target);
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\endcode
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We have a length map and a maximum speed map on the arcs of a digraph.
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The minimum time to pass the arc can be calculated as the division of
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the two maps which can be done implicitly with the \c DivMap template
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class. We use the implicit minimum time map as the length map of the
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\c Dijkstra algorithm.
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*/
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/**
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@defgroup paths Path Structures
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@ingroup datas
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\brief %Path structures implemented in LEMON.
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This group contains the path structures implemented in LEMON.
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LEMON provides flexible data structures to work with paths.
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All of them have similar interfaces and they can be copied easily with
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assignment operators and copy constructors. This makes it easy and
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efficient to have e.g. the Dijkstra algorithm to store its result in
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any kind of path structure.
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\sa \ref concepts::Path "Path concept"
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*/
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/**
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@defgroup heaps Heap Structures
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@ingroup datas
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\brief %Heap structures implemented in LEMON.
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This group contains the heap structures implemented in LEMON.
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LEMON provides several heap classes. They are efficient implementations
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of the abstract data type \e priority \e queue. They store items with
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specified values called \e priorities in such a way that finding and
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removing the item with minimum priority are efficient.
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The basic operations are adding and erasing items, changing the priority
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of an item, etc.
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Heaps are crucial in several algorithms, such as Dijkstra and Prim.
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The heap implementations have the same interface, thus any of them can be
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used easily in such algorithms.
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\sa \ref concepts::Heap "Heap concept"
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*/
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/**
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@defgroup matrices Matrices
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@ingroup datas
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\brief Two dimensional data storages implemented in LEMON.
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This group contains two dimensional data storages implemented in LEMON.
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*/
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/**
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@defgroup auxdat Auxiliary Data Structures
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@ingroup datas
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\brief Auxiliary data structures implemented in LEMON.
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This group contains some data structures implemented in LEMON in
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order to make it easier to implement combinatorial algorithms.
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*/
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/**
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@defgroup geomdat Geometric Data Structures
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@ingroup auxdat
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\brief Geometric data structures implemented in LEMON.
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This group contains geometric data structures implemented in LEMON.
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 - \ref lemon::dim2::Point "dim2::Point" implements a two dimensional
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   vector with the usual operations.
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 - \ref lemon::dim2::Box "dim2::Box" can be used to determine the
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   rectangular bounding box of a set of \ref lemon::dim2::Point
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   "dim2::Point"'s.
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*/
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/**
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@defgroup matrices Matrices
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@ingroup auxdat
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\brief Two dimensional data storages implemented in LEMON.
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This group contains two dimensional data storages implemented in LEMON.
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*/
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/**
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@defgroup algs Algorithms
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\brief This group contains the several algorithms
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implemented in LEMON.
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This group contains the several algorithms
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implemented in LEMON.
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*/
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/**
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@defgroup search Graph Search
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@ingroup algs
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\brief Common graph search algorithms.
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This group contains the common graph search algorithms, namely
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\e breadth-first \e search (BFS) and \e depth-first \e search (DFS)
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\ref clrs01algorithms.
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*/
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@@ -427,109 +419,109 @@
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\brief Algorithms for finding minimum cut in graphs.
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This group contains the algorithms for finding minimum cut in graphs.
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The \e minimum \e cut \e problem is to find a non-empty and non-complete
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\f$X\f$ subset of the nodes with minimum overall capacity on
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outgoing arcs. Formally, there is a \f$G=(V,A)\f$ digraph, a
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\f$cap: A\rightarrow\mathbf{R}^+_0\f$ capacity function. The minimum
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cut is the \f$X\f$ solution of the next optimization problem:
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\f[ \min_{X \subset V, X\not\in \{\emptyset, V\}}
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    \sum_{uv\in A: u\in X, v\not\in X}cap(uv) \f]
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LEMON contains several algorithms related to minimum cut problems:
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- \ref HaoOrlin "Hao-Orlin algorithm" for calculating minimum cut
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  in directed graphs.
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- \ref NagamochiIbaraki "Nagamochi-Ibaraki algorithm" for
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  calculating minimum cut in undirected graphs.
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- \ref GomoryHu "Gomory-Hu tree computation" for calculating
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  all-pairs minimum cut in undirected graphs.
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If you want to find minimum cut just between two distinict nodes,
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see the \ref max_flow "maximum flow problem".
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*/
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/**
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@defgroup min_mean_cycle Minimum Mean Cycle Algorithms
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@ingroup algs
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\brief Algorithms for finding minimum mean cycles.
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This group contains the algorithms for finding minimum mean cycles
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\ref clrs01algorithms, \ref amo93networkflows.
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The \e minimum \e mean \e cycle \e problem is to find a directed cycle
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of minimum mean length (cost) in a digraph.
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The mean length of a cycle is the average length of its arcs, i.e. the
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ratio between the total length of the cycle and the number of arcs on it.
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This problem has an important connection to \e conservative \e length
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\e functions, too. A length function on the arcs of a digraph is called
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conservative if and only if there is no directed cycle of negative total
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length. For an arbitrary length function, the negative of the minimum
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cycle mean is the smallest \f$\epsilon\f$ value so that increasing the
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arc lengths uniformly by \f$\epsilon\f$ results in a conservative length
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function.
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LEMON contains three algorithms for solving the minimum mean cycle problem:
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- \ref Karp "Karp"'s original algorithm \ref amo93networkflows,
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- \ref KarpMmc Karp's original algorithm \ref amo93networkflows,
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  \ref dasdan98minmeancycle.
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- \ref HartmannOrlin "Hartmann-Orlin"'s algorithm, which is an improved
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- \ref HartmannOrlinMmc Hartmann-Orlin's algorithm, which is an improved
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  version of Karp's algorithm \ref dasdan98minmeancycle.
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- \ref Howard "Howard"'s policy iteration algorithm
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- \ref HowardMmc Howard's policy iteration algorithm
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  \ref dasdan98minmeancycle.
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In practice, the Howard algorithm proved to be by far the most efficient
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one, though the best known theoretical bound on its running time is
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exponential.
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Both Karp and HartmannOrlin algorithms run in time O(ne) and use space
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O(n<sup>2</sup>+e), but the latter one is typically faster due to the
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applied early termination scheme.
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In practice, the \ref HowardMmc "Howard" algorithm proved 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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run in time O(ne) and use space O(n<sup>2</sup>+e), but the latter one is
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typically faster due to the applied early termination scheme.
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*/
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/**
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@defgroup matching Matching Algorithms
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@ingroup algs
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\brief Algorithms for finding matchings in graphs and bipartite graphs.
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This group contains the algorithms for calculating
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matchings in graphs and bipartite graphs. The general matching problem is
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finding a subset of the edges for which each node has at most one incident
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edge.
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There are several different algorithms for calculate matchings in
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graphs.  The matching problems in bipartite graphs are generally
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easier than in general graphs. The goal of the matching optimization
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can be finding maximum cardinality, maximum weight or minimum cost
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matching. The search can be constrained to find perfect or
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maximum cardinality matching.
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The matching algorithms implemented in LEMON:
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- \ref MaxBipartiteMatching Hopcroft-Karp augmenting path algorithm
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  for calculating maximum cardinality matching in bipartite graphs.
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- \ref PrBipartiteMatching Push-relabel algorithm
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  for calculating maximum cardinality matching in bipartite graphs.
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- \ref MaxWeightedBipartiteMatching
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  Successive shortest path algorithm for calculating maximum weighted
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  matching and maximum weighted bipartite matching in bipartite graphs.
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- \ref MinCostMaxBipartiteMatching
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  Successive shortest path algorithm for calculating minimum cost maximum
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  matching in bipartite graphs.
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- \ref MaxMatching Edmond's blossom shrinking algorithm for calculating
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  maximum cardinality matching in general graphs.
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- \ref MaxWeightedMatching Edmond's blossom shrinking algorithm for calculating
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  maximum weighted matching in general graphs.
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- \ref MaxWeightedPerfectMatching
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  Edmond's blossom shrinking algorithm for calculating maximum weighted
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  perfect matching in general graphs.
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- \ref MaxFractionalMatching Push-relabel algorithm for calculating
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  maximum cardinality fractional matching in general graphs.
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- \ref MaxWeightedFractionalMatching Augmenting path algorithm for calculating
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  maximum weighted fractional matching in general graphs.
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- \ref MaxWeightedPerfectFractionalMatching
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  Augmenting path algorithm for calculating maximum weighted
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  perfect fractional matching in general graphs.
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\image html matching.png
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\image latex matching.eps "Min Cost Perfect Matching" width=\textwidth
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*/
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/* -*- mode: C++; indent-tabs-mode: nil; -*-
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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) 2003-2010
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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_ARG_PARSER_H
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#define LEMON_ARG_PARSER_H
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#include <vector>
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#include <map>
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#include <list>
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#include <string>
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#include <iostream>
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#include <sstream>
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#include <algorithm>
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#include <lemon/assert.h>
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///\ingroup misc
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///\file
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///\brief A tool to parse command line arguments.
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namespace lemon {
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  ///Exception used by ArgParser
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  ///Exception used by ArgParser.
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  ///
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  class ArgParserException : public Exception {
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  public:
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    /// Reasons for failure
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    /// Reasons for failure.
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    ///
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    enum Reason {
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      HELP,         /// <tt>--help</tt> option was given
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      UNKNOWN_OPT,  /// Unknown option was given
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      INVALID_OPT   /// Invalid combination of options
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      HELP,         ///< <tt>--help</tt> option was given.
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      UNKNOWN_OPT,  ///< Unknown option was given.
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      INVALID_OPT   ///< Invalid combination of options.
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    };
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  private:
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    Reason _reason;
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  public:
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    ///Constructor
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    ArgParserException(Reason r) throw() : _reason(r) {}
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    ///Virtual destructor
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    virtual ~ArgParserException() throw() {}
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    ///A short description of the exception
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    virtual const char* what() const throw() {
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      switch(_reason)
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        {
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        case HELP:
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          return "lemon::ArgParseException: ask for help";
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          break;
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        case UNKNOWN_OPT:
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          return "lemon::ArgParseException: unknown option";
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          break;
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        case INVALID_OPT:
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          return "lemon::ArgParseException: invalid combination of options";
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          break;
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        }
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      return "";
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    }
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    ///Return the reason for the failure
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    Reason reason() const {return _reason; }
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  };
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  ///Command line arguments parser
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  ///\ingroup misc
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  ///Command line arguments parser.
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  ///
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  ///For a complete example see the \ref arg_parser_demo.cc demo file.
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  class ArgParser {
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    static void _showHelp(void *p);
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  protected:
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    int _argc;
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    const char * const *_argv;
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    enum OptType { UNKNOWN=0, BOOL=1, STRING=2, DOUBLE=3, INTEGER=4, FUNC=5 };
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    class ParData {
Ignore white space 6 line context
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/* -*- mode: C++; indent-tabs-mode: nil; -*-
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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) 2003-2010
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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_HARTMANN_ORLIN_MMC_H
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#define LEMON_HARTMANN_ORLIN_MMC_H
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/// \ingroup min_mean_cycle
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///
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/// \file
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/// \brief Hartmann-Orlin's algorithm for finding a minimum mean cycle.
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#include <vector>
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#include <limits>
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#include <lemon/core.h>
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#include <lemon/path.h>
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#include <lemon/tolerance.h>
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#include <lemon/connectivity.h>
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namespace lemon {
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  /// \brief Default traits class of HartmannOrlinMmc class.
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  ///
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  /// Default traits class of HartmannOrlinMmc class.
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  /// \tparam GR The type of the digraph.
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  /// \tparam CM The type of the cost map.
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  /// It must conform to the \ref concepts::Rea_data "Rea_data" concept.
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  /// It must conform to the \ref concepts::ReadMap "ReadMap" concept.
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#ifdef DOXYGEN
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  template <typename GR, typename CM>
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#else
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  template <typename GR, typename CM,
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    bool integer = std::numeric_limits<typename CM::Value>::is_integer>
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#endif
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  struct HartmannOrlinMmcDefaultTraits
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  {
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    /// The type of the digraph
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    typedef GR Digraph;
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    /// The type of the cost map
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    typedef CM CostMap;
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    /// The type of the arc costs
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    typedef typename CostMap::Value Cost;
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    /// \brief The large cost type used for internal computations
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    ///
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    /// The large cost type used for internal computations.
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    /// It is \c long \c long if the \c Cost type is integer,
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    /// otherwise it is \c double.
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    /// \c Cost must be convertible to \c LargeCost.
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    typedef double LargeCost;
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    /// The tolerance type used for internal computations
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    typedef lemon::Tolerance<LargeCost> Tolerance;
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    /// \brief The path type of the found cycles
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    ///
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    /// The path type of the found cycles.
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    /// It must conform to the \ref lemon::concepts::Path "Path" concept
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    /// and it must have an \c addFront() function.
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    typedef lemon::Path<Digraph> Path;
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  };
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  // Default traits class for integer cost types
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  template <typename GR, typename CM>
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  struct HartmannOrlinMmcDefaultTraits<GR, CM, true>
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  {
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    typedef GR Digraph;
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    typedef CM CostMap;
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    typedef typename CostMap::Value Cost;
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#ifdef LEMON_HAVE_LONG_LONG
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    typedef long long LargeCost;
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#else
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    typedef long LargeCost;
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#endif
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    typedef lemon::Tolerance<LargeCost> Tolerance;
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    typedef lemon::Path<Digraph> Path;
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  };
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  /// \addtogroup min_mean_cycle
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  /// @{
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  /// \brief Implementation of the Hartmann-Orlin algorithm for finding
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  /// a minimum mean cycle.
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  ///
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  /// This class implements the Hartmann-Orlin algorithm for finding
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  /// a directed cycle of minimum mean cost in a digraph
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  /// \ref amo93networkflows, \ref dasdan98minmeancycle.
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  /// It is an improved version of \ref Karp "Karp"'s original algorithm,
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  /// It is an improved version of \ref KarpMmc "Karp"'s original algorithm,
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  /// it applies an efficient early termination scheme.
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  /// It runs in time O(ne) and uses space O(n<sup>2</sup>+e).
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  ///
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  /// \tparam GR The type of the digraph the algorithm runs on.
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  /// \tparam CM The type of the cost map. The default
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  /// map type is \ref concepts::Digraph::ArcMap "GR::ArcMap<int>".
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  /// \tparam TR The traits class that defines various types used by the
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  /// algorithm. By default, it is \ref HartmannOrlinMmcDefaultTraits
111 111
  /// "HartmannOrlinMmcDefaultTraits<GR, CM>".
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  /// In most cases, this parameter should not be set directly,
113 113
  /// consider to use the named template parameters instead.
114 114
#ifdef DOXYGEN
115 115
  template <typename GR, typename CM, typename TR>
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#else
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  template < typename GR,
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             typename CM = typename GR::template ArcMap<int>,
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             typename TR = HartmannOrlinMmcDefaultTraits<GR, CM> >
120 120
#endif
121 121
  class HartmannOrlinMmc
122 122
  {
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  public:
124 124

	
125 125
    /// The type of the digraph
126 126
    typedef typename TR::Digraph Digraph;
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    /// The type of the cost map
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    typedef typename TR::CostMap CostMap;
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    /// The type of the arc costs
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    typedef typename TR::Cost Cost;
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    /// \brief The large cost type
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    ///
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    /// The large cost type used for internal computations.
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    /// By default, it is \c long \c long if the \c Cost type is integer,
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    /// otherwise it is \c double.
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    typedef typename TR::LargeCost LargeCost;
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    /// The tolerance type
140 140
    typedef typename TR::Tolerance Tolerance;
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    /// \brief The path type of the found cycles
143 143
    ///
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    /// The path type of the found cycles.
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    /// Using the \ref HartmannOrlinMmcDefaultTraits "default traits class",
146 146
    /// it is \ref lemon::Path "Path<Digraph>".
147 147
    typedef typename TR::Path Path;
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149 149
    /// The \ref HartmannOrlinMmcDefaultTraits "traits class" of the algorithm
150 150
    typedef TR Traits;
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