IPOPT#

The COIN Ipopt solver (IPOPT) is an open-source solver for large-scale nonlinear continuous optimization. Ipopt uses an interior point method, together with a filter linear search procedure.

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How to use it#

ampl: option solver ipopt; # change the solver
ampl: option ipopt_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 coin # install IPOPT

# 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="ipopt", ipopt_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;

IPOPT solve result codes:

          0- 99 solved: optimal for an optimization problem, feasible for a satisfaction problem
        100-199 solved? solution candidate returned but error likely
        200-299 infeasible
        300-399 unbounded
        400-499 limit
        500-999 failure, no solution returned