HiGHS#

A leading free solver that has evolved from a large-scale optimization project at the University of Edinburgh. HiGHS is open-source software to solve linear programming, mixed-integer programming, and convex quadratic programming models. The framework used by the driver supports automatic reformulation for many expression types; the modeling guide can be found here.

[Read More] [Modeling guide] [Options] [Changes] [Download HiGHS]

How to use it#

ampl: option solver highs; # change the solver
ampl: option highs_options 'option1=value1 option2=value2'; # specify options
ampl: solve; # solve the problem

How to install using amplpy:

# Install Python API for AMPL:
$ python -m pip install amplpy --upgrade

# Install AMPL & solver modules:
$ python -m amplpy.modules install highs # install HiGHS

# Activate your license (e.g., free ampl.com/ce or ampl.com/courses licenses):
$ python -m amplpy.modules activate <your-license-uuid>

How to use:

from amplpy import AMPL
ampl = AMPL()
...
ampl.solve(solver="highs", highs_options="option1=value1 option2=value2")

Learn more about what we have to offer to implement and deploy Optimization in Python.

AMPL APIs are interfaces that allow developers to access the features of the AMPL interpreter from within a programming language. We have APIs available for:

Resources#

Solver options#

Full list of solver options:

More details on solver options: Features guide.

Retrieving solutions#

The outcome of the last optimization is stored in the AMPL parameter solve_result_num and the relative message in solve_result.

display solve_result_num, solve_result;

HiGHS solve result codes can be obtained by running highs -! or ampl: shell "highs -!";:

          0- 99 solved: optimal for an optimization problem, feasible for a satisfaction problem
        100-199 solved? solution candidate returned but error likely
            150 solved? MP solution check failed (option sol:chk:fail)
        200-299 infeasible
        300-349 unbounded, feasible solution returned
        350-399 unbounded, no feasible solution returned
        400-449 limit, feasible: stopped, e.g., on iterations or Ctrl-C
        450-469 limit, problem is either infeasible or unbounded
        470-499 limit, no solution returned
        500-999 failure, no solution returned
            550 failure: numeric issue, no feasible solution

For general information, see MP result codes guide.

Changelog#