lemon: comparison doc/groups.dox

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-:ac0ff3b0658b
+:11af8506a790
 @defgroup search Graph Search
 @ingroup algs
 \brief Common graph search algorithms.
 This group contains the common graph search algorithms, namely
-\e breadth-first \e search (BFS) and \e depth-first \e search (DFS).
+\e breadth-first \e search (BFS) and \e depth-first \e search (DFS)
+\ref clrs01algorithms.
 */
 /**
 @defgroup shortest_path Shortest Path Algorithms
 @ingroup algs
 \brief Algorithms for finding shortest paths.
-This group contains the algorithms for finding shortest paths in digraphs.
+This group contains the algorithms for finding shortest paths in digraphs
+\ref clrs01algorithms.
 - \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,
 @defgroup spantree Minimum Spanning Tree Algorithms
 @ingroup algs
 \brief Algorithms for finding minimum cost spanning trees and arborescences.
 This group contains the algorithms for finding minimum cost spanning
-trees and arborescences.
+trees and arborescences \ref clrs01algorithms.
 */
 /**
 @defgroup max_flow Maximum Flow Algorithms
 @ingroup algs
 \brief Algorithms for finding maximum flows.
 This group contains the algorithms for finding maximum flows and
-feasible circulations.
+feasible circulations \ref clrs01algorithms, \ref amo93networkflows.
 The \e maximum \e flow \e problem is to find a flow of maximum value between
 a single source and a single target. Formally, there is a \f$G=(V,A)\f$
 digraph, a \f$cap: A\rightarrow\mathbf{R}^+_0\f$ capacity function and
 \f$s, t \in V\f$ source and target nodes.
 \f[ \sum_{uv\in A} f(uv) = \sum_{vu\in A} f(vu)
 \quad \forall u\in V\setminus\{s,t\} \f]
 \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 EdmondsKarp Edmonds-Karp algorithm
-- \ref Preflow Goldberg-Tarjan's preflow push-relabel algorithm.
+\ref edmondskarp72theoretical.
-- \ref DinitzSleatorTarjan Dinitz's blocking flow algorithm with dynamic trees.
+- \ref Preflow Goldberg-Tarjan's preflow push-relabel algorithm
-- \ref GoldbergTarjan Preflow push-relabel algorithm with dynamic trees.
+\ref goldberg88newapproach.
+- \ref DinitzSleatorTarjan Dinitz's blocking flow algorithm with dynamic trees
-In most cases the \ref Preflow "Preflow" algorithm provides the
+\ref dinic70algorithm, \ref sleator83dynamic.
+- \ref GoldbergTarjan !Preflow push-relabel algorithm with dynamic trees
+\ref goldberg88newapproach, \ref sleator83dynamic.
+In most cases the \ref 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 Circulation is a preflow push-relabel algorithm implemented directly
 @ingroup algs
 \brief Algorithms for finding minimum cost flows and circulations.
 This group contains the algorithms for finding minimum cost flows and
-circulations. For more information about this problem and its dual
+circulations \ref amo93networkflows. For more information about this
-solution see \ref min_cost_flow "Minimum Cost Flow Problem".
+problem and its dual 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.
+pivot strategies \ref dantzig63linearprog, \ref kellyoneill91netsimplex.
 - \ref CostScaling Push-Relabel and Augment-Relabel algorithms based on
-cost scaling.
+cost scaling \ref goldberg90approximation, \ref goldberg97efficient,
+\ref bunnagel98efficient.
 - \ref CapacityScaling Successive Shortest %Path algorithm with optional
-capacity scaling.
+capacity scaling \ref edmondskarp72theoretical.
-- \ref CancelAndTighten The Cancel and Tighten algorithm.
+- \ref CancelAndTighten The Cancel and Tighten algorithm
-- \ref CycleCanceling Cycle-Canceling algorithms.
+\ref goldberg89cyclecanceling.
+- \ref CycleCanceling Cycle-Canceling algorithms
+\ref klein67primal, \ref goldberg89cyclecanceling.
 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).
 This group contains some general optimization frameworks
 implemented in LEMON.
 */
 /**
-@defgroup lp_group Lp and Mip Solvers
+@defgroup lp_group LP and MIP Solvers
 @ingroup gen_opt_group
-\brief Lp and Mip solver interfaces for LEMON.
+\brief LP and MIP solver interfaces for LEMON.
-This group contains Lp and Mip solver interfaces for LEMON. The
+This group contains LP and MIP solver interfaces for LEMON.
-various LP solvers could be used in the same manner with this
+Various LP solvers could be used in the same manner with this
-interface.
+high-level interface.
+The currently supported solvers are \ref glpk, \ref clp, \ref cbc,
+\ref cplex, \ref soplex.
 */
 /**
 @defgroup lp_utils Tools for Lp and Mip Solvers
 @ingroup lp_group

changeset 803	53bea38f71cb
parent 789	8e68671af789
child 817	432c54cec63c