GLPK 2.3 (release date: Apr 09, 2001)

        New edition of the document "GLPK User's Guide" is included in
        the distribution. Now it describes all additional API routines
        which were recently added to the package.

        The MIP solver was fully re-programmed in order to improve its
        robustness and performance. In particular, a basis recovering
        procedure was implemented (this procedure allows switching to
        the primal simplex method in case when the dual simplex method
        fails).

GLPK 2.2 (release date: Mar 15, 2001)

        Now GLPK includes a tentative implementation of the
        branch-and-bound procedure based on the dual simplex method for
        mixed integer linear programming (MIP).

        Complete description of this new feature of the package is given
        in the preliminary document "Mixed Integer Linear Programming
        Using GLPK Version 2.2 (Supplement to GLPK User's Guide)". This
        document is included into the distribution in plain text format
        (see the file 'mip.txt' in the subdirectory 'doc').

        The MIP solver (glp_integer) can be used as GLPK API routine in
        the same way as the pure LP solver (glp_simplex).

        The stand-alone program 'glpsol' is now able to solve LP as well
        as MIP problems.

        Note that the current version of GLPK MIP solver is based on
        easiest heuristics for branching and backtrackng. Therefore the
        solver is fit mainly for MIP problems which are not very hard
        and have few integer variables.

GLPK 2.1 (release date: Feb 19, 2001)

        The document "GLPK Implementation of the Revised Simplex Method"
        is included into the distribution. This document describes most
        of routines related to the revised simplex method.

GLPK 2.0 (release date: Jan 25, 2001)

        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.
