GLPK 2.0 (release date: Jan 25, 2000)

        Now GLPK includes a tentative implementation of the primal-dual
        interior point method for large-scale linear programming.

        The interior point solver can be used as GLPK API routine in the
        same manner as the simplex method solver (glp_simplex):

        ret = glp_interior();

        Note that currently the interior point solver implemented in
        GLPK doesn't include many important features, in particular:

        * it can't process dense columns; therefore if the problem has
          dense columns, the solving will be extremely inefficient;

        * it has no special features against numerical unstability;
          some problems may cause premature termination of the solving
          when the matrix A*D*A' becomes ill-conditioned;

        * it computes only values of primal (auxiliary and structural)
          variables and doesn't compute values of dual variables (i.e.
          reduced costs) which are just set to zero;

        * it doesn't identify optimal basis corresponding to the found
          interior point solution; all variables in the found solution
          are just marked as basic variables.

        GLPK also includes a stand-alone program 'glpipm' which is a
        demo based on the interior point method. It may be used in the
        same way as the program 'glpsol' that is based on the simplex
        method.

        All routines related to the implementation of the interior point
        method are not documented yet. The author plans to document them
        in the nearest future.
