GEKKO Optimization Suite
=======================================



Overview
--------

`GEKKO is a Python package for machine learning and optimization <https://machinelearning.byu.edu>`_ of mixed-integer and
differential algebraic equations. It is coupled with large-scale solvers for
linear, quadratic, nonlinear, and mixed integer programming (LP, QP, NLP, MILP,
MINLP). Modes of operation include parameter regression, data reconciliation, real-time optimization,
dynamic simulation, and nonlinear predictive control. GEKKO is an object-oriented Python library to facilitate local execution of APMonitor.

More of the backend details are available at :ref:`what_APM_does` and in the `GEKKO Journal Article <https://www.mdpi.com/2227-9717/6/8/106>`_. Example applications are available to `get started with GEKKO <https://apmonitor.com/wiki/index.php/Main/GekkoPythonOptimization>`_. 

Installation
------------

A pip package is available (see `current download stats <https://pypistats.org/packages/gekko>`_)::

	pip install gekko

Use the **----user** option to install if there is a permission error because Python is installed for all users and the account lacks administrative priviledge. You can upgrade from the command line with the upgrade flag::

    pip install --upgrade gekko
    
Another method is to install in a Jupyter notebook with **!pip install gekko** or with Python code, although this is not the preferred method::

    try:
        from pip import main as pipmain
    except:
        from pip._internal import main as pipmain
    pipmain(['install','gekko'])

Project Support
------------

There are GEKKO tutorials and documentation in:

- `GitHub Repository (examples folder) <https://github.com/BYU-PRISM/GEKKO/tree/master/examples>`_
- `Dynamic Optimization Course <https://apmonitor.com/do>`_
- `APMonitor Documentation <https://apmonitor.com/wiki>`_
- `GEKKO Documentation <https://gekko.readthedocs.io/en/latest/examples.html>`_
- `18 Example Applications with Videos <https://apmonitor.com/wiki/index.php/Main/GekkoPythonOptimization>`_

For project specific help, search in the `GEKKO topic tags on StackOverflow <https://stackoverflow.com/questions/tagged/gekko>`_. If there isn't a similar solution, please consider posting a question with a `Mimimal, Complete, and Verifiable example <https://stackoverflow.com/help/mcve>`_. If you give the question a `GEKKO tag with [gekko] <https://stackoverflow.com/help/tagging>`_, the subscribed community is alerted to your question.

Citing GEKKO
---------------------

If you use GEKKO in your work, please cite the following paper:

	Beal, L.D.R., Hill, D., Martin, R.A., and Hedengren, J. D., GEKKO Optimization Suite, Processes, Volume 6, Number 8, 2018, doi: 10.3390/pr6080106. 

The BibTeX entry is::

	@article{beal2018gekko,
	title={GEKKO Optimization Suite},
	author={Beal, Logan and Hill, Daniel and Martin, R and Hedengren, John},
	journal={Processes},
	volume={6},
	number={8},
	pages={106},
	year={2018},
	doi={10.3390/pr6080106},
	publisher={Multidisciplinary Digital Publishing Institute}}

Contents
--------

.. toctree::
	:maxdepth: 1

	overview
	quick_start
	imode
	global
	tuning_params
	MV_options
	CV_options
	model_methods
	brain
	ml
	chemical
	solver_extension
	examples
	support

A PDF of the complete Gekko (stable release) documentation is available from this `link <https://gekko.readthedocs.io/_/downloads/en/stable/pdf/>`_.

Overview of GEKKO
--------

.. raw:: html

    <div style="position: relative; padding-bottom: 56.25%; height: 0; overflow: hidden; max-width: 100%; height: auto;">
        <iframe src="//www.youtube.com/embed/bXAkr7MPf4w" frameborder="0" allowfullscreen style="position: absolute; top: 0; left: 0; width: 100%; height: 100%;"></iframe>
    </div>