Index: .hgtags
===================================================================
--- .hgtags	(revision 671)
+++ .hgtags	(revision 671)
@@ -0,0 +1,1 @@
+06f816565bef381024acd7c15beb74ba407e3546 r1.1
Index: doc/groups.dox
===================================================================
--- doc/groups.dox	(revision 661)
+++ doc/groups.dox	(revision 664)
@@ -227,12 +227,4 @@
 
 /**
-@defgroup matrices Matrices
-@ingroup datas
-\brief Two dimensional data storages implemented in LEMON.
-
-This group contains two dimensional data storages implemented in LEMON.
-*/
-
-/**
 @defgroup paths Path Structures
 @ingroup datas
@@ -284,14 +276,6 @@
 This group contains the algorithms for finding shortest paths in digraphs.
 
- - \ref Dijkstra algorithm for finding shortest paths from a source node
-   when all arc lengths are non-negative.
- - \ref BellmanFord "Bellman-Ford" algorithm for finding shortest paths
-   from a source node when arc lenghts can be either positive or negative,
-   but the digraph should not contain directed cycles with negative total
-   length.
- - \ref FloydWarshall "Floyd-Warshall" and \ref Johnson "Johnson" algorithms
-   for solving the \e all-pairs \e shortest \e paths \e problem when arc
-   lenghts can be either positive or negative, but the digraph should
-   not contain directed cycles with negative total length.
+ - \ref Dijkstra Dijkstra's algorithm for finding shortest paths from a 
+   source node when all arc lengths are non-negative.
  - \ref Suurballe A successive shortest path algorithm for finding
    arc-disjoint paths between two nodes having minimum total length.
@@ -318,14 +302,8 @@
 \f[ 0 \leq f(uv) \leq cap(uv) \quad \forall uv\in A \f]
 
-LEMON contains several algorithms for solving maximum flow problems:
-- \ref EdmondsKarp Edmonds-Karp algorithm.
-- \ref Preflow Goldberg-Tarjan's preflow push-relabel algorithm.
-- \ref DinitzSleatorTarjan Dinitz's blocking flow algorithm with dynamic trees.
-- \ref GoldbergTarjan Preflow push-relabel algorithm with dynamic trees.
-
-In most cases the \ref Preflow "Preflow" algorithm provides the
-fastest method for computing a maximum flow. All implementations
-also provide functions to query the minimum cut, which is the dual
-problem of maximum flow.
+\ref Preflow implements the preflow push-relabel algorithm of Goldberg and
+Tarjan for solving this problem. It also provides functions to query the
+minimum cut, which is the dual problem of maximum flow.
+
 
 \ref Circulation is a preflow push-relabel algorithm implemented directly 
@@ -345,18 +323,7 @@
 solution see \ref min_cost_flow "Minimum Cost Flow Problem".
 
-LEMON contains several algorithms for this problem.
- - \ref NetworkSimplex Primal Network Simplex algorithm with various
-   pivot strategies.
- - \ref CostScaling Push-Relabel and Augment-Relabel algorithms based on
-   cost scaling.
- - \ref CapacityScaling Successive Shortest %Path algorithm with optional
-   capacity scaling.
- - \ref CancelAndTighten The Cancel and Tighten algorithm.
- - \ref CycleCanceling Cycle-Canceling algorithms.
-
-In general NetworkSimplex is the most efficient implementation,
-but in special cases other algorithms could be faster.
-For example, if the total supply and/or capacities are rather small,
-CapacityScaling is usually the fastest algorithm (without effective scaling).
+\ref NetworkSimplex is an efficient implementation of the primal Network
+Simplex algorithm for finding minimum cost flows. It also provides dual
+solution (node potentials), if an optimal flow is found.
 */
 
@@ -382,6 +349,4 @@
 - \ref HaoOrlin "Hao-Orlin algorithm" for calculating minimum cut
   in directed graphs.
-- \ref NagamochiIbaraki "Nagamochi-Ibaraki algorithm" for
-  calculating minimum cut in undirected graphs.
 - \ref GomoryHu "Gomory-Hu tree computation" for calculating
   all-pairs minimum cut in undirected graphs.
@@ -404,28 +369,14 @@
 
 /**
-@defgroup planar Planarity Embedding and Drawing
-@ingroup algs
-\brief Algorithms for planarity checking, embedding and drawing
-
-This group contains the algorithms for planarity checking,
-embedding and drawing.
-
-\image html planar.png
-\image latex planar.eps "Plane graph" width=\textwidth
-*/
-
-/**
 @defgroup matching Matching Algorithms
 @ingroup algs
 \brief Algorithms for finding matchings in graphs and bipartite graphs.
 
-This group contains the algorithms for calculating
-matchings in graphs and bipartite graphs. The general matching problem is
-finding a subset of the edges for which each node has at most one incident
-edge.
+This group contains the algorithms for calculating matchings in graphs.
+The general matching problem is finding a subset of the edges for which
+each node has at most one incident edge.
 
 There are several different algorithms for calculate matchings in
-graphs.  The matching problems in bipartite graphs are generally
-easier than in general graphs. The goal of the matching optimization
+graphs. The goal of the matching optimization
 can be finding maximum cardinality, maximum weight or minimum cost
 matching. The search can be constrained to find perfect or
@@ -433,14 +384,4 @@
 
 The matching algorithms implemented in LEMON:
-- \ref MaxBipartiteMatching Hopcroft-Karp augmenting path algorithm
-  for calculating maximum cardinality matching in bipartite graphs.
-- \ref PrBipartiteMatching Push-relabel algorithm
-  for calculating maximum cardinality matching in bipartite graphs.
-- \ref MaxWeightedBipartiteMatching
-  Successive shortest path algorithm for calculating maximum weighted
-  matching and maximum weighted bipartite matching in bipartite graphs.
-- \ref MinCostMaxBipartiteMatching
-  Successive shortest path algorithm for calculating minimum cost maximum
-  matching in bipartite graphs.
 - \ref MaxMatching Edmond's blossom shrinking algorithm for calculating
   maximum cardinality matching in general graphs.
@@ -474,13 +415,4 @@
 
 /**
-@defgroup approx Approximation Algorithms
-@ingroup algs
-\brief Approximation algorithms.
-
-This group contains the approximation and heuristic algorithms
-implemented in LEMON.
-*/
-
-/**
 @defgroup gen_opt_group General Optimization Tools
 \brief This group contains some general optimization frameworks
@@ -499,21 +431,4 @@
 various LP solvers could be used in the same manner with this
 interface.
-*/
-
-/**
-@defgroup lp_utils Tools for Lp and Mip Solvers
-@ingroup lp_group
-\brief Helper tools to the Lp and Mip solvers.
-
-This group adds some helper tools to general optimization framework
-implemented in LEMON.
-*/
-
-/**
-@defgroup metah Metaheuristics
-@ingroup gen_opt_group
-\brief Metaheuristics for LEMON library.
-
-This group contains some metaheuristic optimization tools.
 */
 
Index: lemon/suurballe.h
===================================================================
--- lemon/suurballe.h	(revision 615)
+++ lemon/suurballe.h	(revision 644)
@@ -46,6 +46,6 @@
   /// Note that this problem is a special case of the \ref min_cost_flow
   /// "minimum cost flow problem". This implementation is actually an
-  /// efficient specialized version of the \ref CapacityScaling
-  /// "Successive Shortest Path" algorithm directly for this problem.
+  /// efficient specialized version of the Successive Shortest Path
+  /// algorithm directly for this problem.
   /// Therefore this class provides query functions for flow values and
   /// node potentials (the dual solution) just like the minimum cost flow
