HiGHS is a high performance serial and parallel solver for large scale
sparse linear optimization problems of the form
Minimize (1/2) x^TQx + c^Tx subject to L <= Ax <= U; l <= x <= u
where Q must be positive semi-definite and, if Q is zero, there may be a
requirement that some of the variables take integer values. Thus HiGHS
can solve linear programming (LP) problems, convex quadratic programming
(QP) problems, and mixed integer programming (MIP) problems. It is
mainly written in C++, but also has some C.
HiGHS has primal and dual revised simplex solvers, originally written by
Qi Huangfu and further developed by Julian Hall. It also has an
interior point solver for LP written by Lukas Schork, an active set
solver for QP written by Michael Feldmeier, and a MIP solver written by
Leona Gottwald. Other features have been added by Julian Hall and Ivet
Galabova, who manages the software engineering of HiGHS and interfaces
to C, C#, FORTRAN, Julia and Python.
Although HiGHS is freely available under the MIT license, we would be
pleased to learn about users' experience and give advice via email sent
to highsopt@gmail.com.
* Wed Jul 03 2024 Jerry James <loganjerry@gmail.com> - 1.7.2-1
- Version 1.7.2
* Wed Jun 19 2024 Jerry James <loganjerry@gmail.com> - 1.7.1-1
- Version 1.7.1
- Drop upstreamed pybind11 and examples patches
- Generate a man page for the highs binary
* Sat Jun 08 2024 Python Maint <python-maint@redhat.com> - 1.7.0-2
- Rebuilt for Python 3.13
* Tue Mar 19 2024 Jerry James <loganjerry@gmail.com> - 1.7.0-1
- Version 1.7.0
- Drop unnecessary githash patch
- Add patch to avoid downloading pybind11 at build time
- Add patch to fix building examples
- Test with pytest
* Fri Feb 23 2024 Jerry James <loganjerry@gmail.com> - 1.6.0-1
- Initial RPM
