1.1 --- a/doc/groups.dox Fri Aug 09 11:28:17 2013 +0200
1.2 +++ b/doc/groups.dox Fri Aug 09 11:29:40 2013 +0200
1.3 @@ -422,7 +422,8 @@
1.4 nodes or above), especially if they are sparse.
1.5 However, other algorithms could be faster in special cases.
1.6 For example, if the total supply and/or capacities are rather small,
1.7 -\ref CapacityScaling is usually the fastest algorithm (without effective scaling).
1.8 +\ref CapacityScaling is usually the fastest algorithm
1.9 +(without effective scaling).
1.10
1.11 These classes are intended to be used with integer-valued input data
1.12 (capacities, supply values, and costs), except for \ref CapacityScaling,
2.1 --- a/lemon/concepts/digraph.h Fri Aug 09 11:28:17 2013 +0200
2.2 +++ b/lemon/concepts/digraph.h Fri Aug 09 11:29:40 2013 +0200
2.3 @@ -312,7 +312,9 @@
2.4
2.5 /// Sets the iterator to the first arc of the given digraph.
2.6 ///
2.7 - explicit ArcIt(const Digraph& g) { ::lemon::ignore_unused_variable_warning(g); }
2.8 + explicit ArcIt(const Digraph& g) {
2.9 + ::lemon::ignore_unused_variable_warning(g);
2.10 + }
2.11 /// Sets the iterator to the given arc.
2.12
2.13 /// Sets the iterator to the given arc of the given digraph.
3.1 --- a/lemon/concepts/graph.h Fri Aug 09 11:28:17 2013 +0200
3.2 +++ b/lemon/concepts/graph.h Fri Aug 09 11:29:40 2013 +0200
3.3 @@ -396,7 +396,9 @@
3.4
3.5 /// Sets the iterator to the first arc of the given graph.
3.6 ///
3.7 - explicit ArcIt(const Graph &g) { ::lemon::ignore_unused_variable_warning(g); }
3.8 + explicit ArcIt(const Graph &g) {
3.9 + ::lemon::ignore_unused_variable_warning(g);
3.10 + }
3.11 /// Sets the iterator to the given arc.
3.12
3.13 /// Sets the iterator to the given arc of the given graph.
4.1 --- a/lemon/cost_scaling.h Fri Aug 09 11:28:17 2013 +0200
4.2 +++ b/lemon/cost_scaling.h Fri Aug 09 11:29:40 2013 +0200
4.3 @@ -91,7 +91,8 @@
4.4 ///
4.5 /// \ref CostScaling implements a cost scaling algorithm that performs
4.6 /// push/augment and relabel operations for finding a \ref min_cost_flow
4.7 - /// "minimum cost flow" \cite amo93networkflows, \cite goldberg90approximation,
4.8 + /// "minimum cost flow" \cite amo93networkflows,
4.9 + /// \cite goldberg90approximation,
4.10 /// \cite goldberg97efficient, \cite bunnagel98efficient.
4.11 /// It is a highly efficient primal-dual solution method, which
4.12 /// can be viewed as the generalization of the \ref Preflow
4.13 @@ -213,7 +214,8 @@
4.14 typedef std::vector<Cost> CostVector;
4.15 typedef std::vector<LargeCost> LargeCostVector;
4.16 typedef std::vector<char> BoolVector;
4.17 - // Note: vector<char> is used instead of vector<bool> for efficiency reasons
4.18 + // Note: vector<char> is used instead of vector<bool>
4.19 + // for efficiency reasons
4.20
4.21 private:
4.22
5.1 --- a/lemon/howard_mmc.h Fri Aug 09 11:28:17 2013 +0200
5.2 +++ b/lemon/howard_mmc.h Fri Aug 09 11:29:40 2013 +0200
5.3 @@ -361,7 +361,8 @@
5.4 ///
5.5 /// \return The termination cause of the search process.
5.6 /// For more information, see \ref TerminationCause.
5.7 - TerminationCause findCycleMean(int limit = std::numeric_limits<int>::max()) {
5.8 + TerminationCause findCycleMean(int limit =
5.9 + std::numeric_limits<int>::max()) {
5.10 // Initialize and find strongly connected components
5.11 init();
5.12 findComponents();
6.1 --- a/lemon/max_cardinality_search.h Fri Aug 09 11:28:17 2013 +0200
6.2 +++ b/lemon/max_cardinality_search.h Fri Aug 09 11:29:40 2013 +0200
6.3 @@ -164,8 +164,8 @@
6.4 /// \brief Instantiates a CardinalityMap.
6.5 ///
6.6 /// This function instantiates a \ref CardinalityMap.
6.7 - /// \param digraph is the digraph, to which we would like to define the \ref
6.8 - /// CardinalityMap
6.9 + /// \param digraph is the digraph, to which we would like to
6.10 + /// define the \ref CardinalityMap
6.11 static CardinalityMap *createCardinalityMap(const Digraph &digraph) {
6.12 return new CardinalityMap(digraph);
6.13 }
6.14 @@ -180,7 +180,8 @@
6.15 /// This class provides an efficient implementation of Maximum Cardinality
6.16 /// Search algorithm. The maximum cardinality search first chooses any
6.17 /// node of the digraph. Then every time it chooses one unprocessed node
6.18 - /// with maximum cardinality, i.e the sum of capacities on out arcs to the nodes
6.19 + /// with maximum cardinality, i.e the sum of capacities on out arcs
6.20 + /// to the nodes
6.21 /// which were previusly processed.
6.22 /// If there is a cut in the digraph the algorithm should choose
6.23 /// again any unprocessed node of the digraph.
7.1 --- a/test/tsp_test.cc Fri Aug 09 11:28:17 2013 +0200
7.2 +++ b/test/tsp_test.cc Fri Aug 09 11:29:40 2013 +0200
7.3 @@ -66,12 +66,13 @@
7.4 FullGraph::NodeMap<bool> used(gr, false);
7.5
7.6 int node_cnt = 0;
7.7 - for (typename Container::const_iterator it = p.begin(); it != p.end(); ++it) {
7.8 - FullGraph::Node node = *it;
7.9 - if (used[node]) return false;
7.10 - used[node] = true;
7.11 - ++node_cnt;
7.12 - }
7.13 + for (typename Container::const_iterator it = p.begin(); it != p.end(); ++it)
7.14 + {
7.15 + FullGraph::Node node = *it;
7.16 + if (used[node]) return false;
7.17 + used[node] = true;
7.18 + ++node_cnt;
7.19 + }
7.20
7.21 return (node_cnt == gr.nodeNum());
7.22 }
7.23 @@ -264,8 +265,10 @@
7.24 tspTestSmall<NearestNeighborTsp<ConstMap<Edge, int> > >("Nearest Neighbor");
7.25 tspTestSmall<GreedyTsp<ConstMap<Edge, int> > >("Greedy");
7.26 tspTestSmall<NearestInsertionTsp<ConstMap<Edge, int> > >("Nearest Insertion");
7.27 - tspTestSmall<FarthestInsertionTsp<ConstMap<Edge, int> > >("Farthest Insertion");
7.28 - tspTestSmall<CheapestInsertionTsp<ConstMap<Edge, int> > >("Cheapest Insertion");
7.29 + tspTestSmall<FarthestInsertionTsp<ConstMap<Edge, int> > >
7.30 + ("Farthest Insertion");
7.31 + tspTestSmall<CheapestInsertionTsp<ConstMap<Edge, int> > >
7.32 + ("Cheapest Insertion");
7.33 tspTestSmall<RandomInsertionTsp<ConstMap<Edge, int> > >("Random Insertion");
7.34 tspTestSmall<ChristofidesTsp<ConstMap<Edge, int> > >("Christofides");
7.35 tspTestSmall<Opt2Tsp<ConstMap<Edge, int> > >("2-opt");
8.1 --- a/tools/dimacs-solver.cc Fri Aug 09 11:28:17 2013 +0200
8.2 +++ b/tools/dimacs-solver.cc Fri Aug 09 11:29:40 2013 +0200
8.3 @@ -127,7 +127,8 @@
8.4 typename MCF::ProblemType res = ns.run();
8.5 if (report) {
8.6 std::cerr << "Run NetworkSimplex: " << ti << "\n\n";
8.7 - std::cerr << "Feasible flow: " << (res == MCF::OPTIMAL ? "found" : "not found") << '\n';
8.8 + std::cerr << "Feasible flow: " << (res == MCF::OPTIMAL ? "found" :
8.9 + "not found") << '\n';
8.10 if (res) std::cerr << "Min flow cost: "
8.11 << ns.template totalCost<LargeValue>() << '\n';
8.12 }