diff --git a/Polygonal_surface_reconstruction/doc/Polygonal_surface_reconstruction/Polygonal_surface_reconstruction.txt b/Polygonal_surface_reconstruction/doc/Polygonal_surface_reconstruction/Polygonal_surface_reconstruction.txt index 935c58f4813..cbaf4f3e5a1 100644 --- a/Polygonal_surface_reconstruction/doc/Polygonal_surface_reconstruction/Polygonal_surface_reconstruction.txt +++ b/Polygonal_surface_reconstruction/doc/Polygonal_surface_reconstruction/Polygonal_surface_reconstruction.txt @@ -208,7 +208,7 @@ The current implementation incorporates two open source solvers: \ref thirdparty (see \ref PkgSolverInterface). It should be noted that GLPK only manages to solve small problems, i.e., objects with reasonably simple structure. In case you are reconstructing more complex objects, you may need to consider more efficient open source -solvers (e.g., CBC) or even commercial solvers (e.g., +solvers (e.g., CBC) or even commercial solvers (e.g., Gurobi, CPLEX). The following table gives a rough idea of the performance of some solvers. diff --git a/Solver_interface/include/CGAL/Mixed_integer_program_traits.h b/Solver_interface/include/CGAL/Mixed_integer_program_traits.h index 1af990c3cf3..472e6dbc609 100644 --- a/Solver_interface/include/CGAL/Mixed_integer_program_traits.h +++ b/Solver_interface/include/CGAL/Mixed_integer_program_traits.h @@ -273,7 +273,7 @@ namespace CGAL { /// classes, i.e., `CGAL::GLPK_mixed_integer_program_traits` or /// `CGAL::SCIP_mixed_integer_program_traits`. Alternatively, use /// `CGAL::Mixed_integer_program_traits` as a base to derive a new model - /// (using e.g., CBC , + /// (using e.g., CBC , /// Gurobi for better /// performance). ///