APMonitor / GEKKO Support
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Generative AI is built into Gekko with the support module. Create a support agent with support.agent() and then ask any questions about Gekko.
(:source lang=python:) from gekko import support a = support.agent() a.ask("Can you optimize the Rosenbrock function?") (:sourceend:)
Prior questions and answers are stored as context for follow-up questions.
There are several opportunities to get involved in the community of users. The newest and most capable optimization suite is the Python GEKKO package that is available with
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There are several ways to get involved in the community of GEKKO users. The newest and most capable interface to APMonitor is the Python GEKKO package that is available with:
Gekko runs in Python or as a function call from MATLAB.
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Help with a Project
As a first step, please search in the e-mail discussion group below or for the GEKKO topic tags on StackOverflow. If there isn't a solution, please consider posting a question with a Mimimal, Complete, and Verifiable example. If you give it a GEKKO tag with [gekko], the subscribed community will be alerted to your question and be able to give a quicker response.
Gekko Support
As a first step, please search GEKKO topic tags on StackOverflow. If there isn't a solution, please consider posting a question with a Mimimal, Complete, and Verifiable example. If you give it a GEKKO tag with [gekko], the subscribed community will be alerted to your question.
These tools are for solving Mixed Integer Nonlinear Programming (MINLP) problems with differential or algebraic constraints. There are a number of places to get additional information about <font color="#000099">A</font><font color="#ff0000">P</font>Monitor. There is the web-site at <a href="https://apmonitor.com/">https://apmonitor.com</a>. Example problems are posted to the introductory page for the web-based trial.
These tools are for solving Mixed Integer Nonlinear Programming (MINLP) problems with differential or algebraic constraints. There are a number of places to get additional information about <font color="#000099">A</font><font color="#ff0000">P</font>Monitor. There is the web-site at <a href="https://apmonitor.com/">https://apmonitor.com</a> with example problems in the online courses and documentation.
<p>Experienced <b>AIMMS</b>, <b>AMPL</b>, <b>GAMS</b>, <b>Modelica</b>, or <b>gProms</b> users will likely find the modeling language easy to learn. These tools are for solving Mixed Integer Nonlinear Programming (MINLP) problems. There are a number of software tools that can solve differential and algebraic equations (DAEs). These include <b>gProms</b>, <b>MATLAB</b>, <b>Modellica</b>, and others. <a href="https://apmonitor.com/compare.htm">A comparison of a gravity drained water tank model</a> is used a benchmark for these modeling languages. These software tools are very good at providing a flexible environment for DAE simulation. New users are generally impressed by the similarity to their native environments, the open-equation format, and performance gains for large-scale model simulation and optimization.</p> <p> </p> <p>There are a number of places to get additional information about <font color="#000099">A</font><font color="#ff0000">P</font>Monitor. There is the web-site at <a href="https://apmonitor.com/">https://apmonitor.com</a>. Some example problems are posted to the introductory page for the web-based trial. For those who want a quick start trial with the software, the easiest way is to submit a model at the <a href="https://apmonitor.com/online/view_pass.php">on-line interface</a>. Selecting the "Instructions" link will lead you to the <a href="https://apmonitor.com/sandbox/instructions.htm">tutorial examples</a> for new users.</p>
These tools are for solving Mixed Integer Nonlinear Programming (MINLP) problems with differential or algebraic constraints. There are a number of places to get additional information about <font color="#000099">A</font><font color="#ff0000">P</font>Monitor. There is the web-site at <a href="https://apmonitor.com/">https://apmonitor.com</a>. Example problems are posted to the introductory page for the web-based trial.
There are several opportunities to get involved in the community of users. The newest and most capable optimization suite is the Python GEKKO package that is available with
To request an enhancement or report a bug, please consider submitting to the issue tracking in the GEKKO Github Repository. If it is a MATLAB/Simulink enhancement or bug report, please send a message to the e-mail user group.
To request an enhancement or report a bug, please consider submitting to the issue tracking in the GEKKO Github Repository.
Two additional opportunities for support include regular Webinars from leading experts and with a discussion forum where questions can be posted or answered with the Google Group: apmonitor@googlegroups.com (Visit discussion group).
Discussion Forum
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document.getElementById('forum_embed').src = 'https://groups.google.com/forum/embed/?place=forum/apmonitor' + '&showsearch=true&showpopout=true&showtabs=false' + '&parenturl=' + encodeURIComponent(window.location.href);
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(:source lang=python:) pip install gekko (:sourceend:)
pip install gekko
(:source lang=python:) pip install gekko (:sourceend:)
(:title APMonitor / GEKKO Support and Discussion Forum:)
(:title APMonitor / GEKKO Support:)
As a first step, please search in the e-mail discussion group below or for the GEKKO topic tags on StackOverflow. If there isn't a solution, please consider posting a question with a Mimimal, Complete, and Verifiable example. If you give it a GEKKO tag, the subscribed community will be alerted to your question and be able to give a quicker response.
As a first step, please search in the e-mail discussion group below or for the GEKKO topic tags on StackOverflow. If there isn't a solution, please consider posting a question with a Mimimal, Complete, and Verifiable example. If you give it a GEKKO tag with [gekko], the subscribed community will be alerted to your question and be able to give a quicker response.
(:title APMonitor Discussion Forum:) (:keywords nonlinear, model, predictive control, APMonitor, differential, algebraic, modeling language, discussion forum:) (:description Visit the APMonitor discussion forum to browse common answers and connect with other researchers in dynamic optimization, estimation, and modeling.:)
(:title APMonitor / GEKKO Support and Discussion Forum:) (:keywords nonlinear, model, predictive control, GEKKO, Python, MATLAB, APMonitor, differential, algebraic, modeling language, discussion forum:) (:description Visit the APMonitor and Python GEKKO discussion forum to browse common answers and connect with other researchers in dynamic optimization, estimation, and modeling.:)
Feature Request or Bug Report
To request an enhancement or report a bug, please consider submitting to the issue tracking in the GEKKO Github Repository. If it is a MATLAB/Simulink enhancement or bug report, please send a message to the e-mail user group.
APMonitor and GEKKO Tutorials
There are many APMonitor and GEKKO tutorials that are in the Dynamic Optimization Course, APMonitor Documentation, and GEKKO Documentation.
Help with a Project
As a first step, please search in the e-mail discussion group below or for the GEKKO topic tags on StackOverflow. If there isn't a solution, please consider posting a question with a Mimimal, Complete, and Verifiable example. If you give it a GEKKO tag, the subscribed community will be alerted to your question and be able to give a quicker response.
Two additional opportunities for support include regular Webinars from leading experts and with a discussion forum where questions can be posted or answered with the Google Group: apmonitor@googlegroups.com (Visit discussion group).
(:description APMonitor Google Groups Discussion Forum:)
(:description Visit the APMonitor discussion forum to browse common answers and connect with other researchers in dynamic optimization, estimation, and modeling.:)
<p>Experienced <b>AIMMS</b>, <b>AMPL</b>, or <b>GAMS</b> users will likely find the modeling language easy to learn. These tools are for solving Mixed Integer Nonlinear Programming (MINLP) problems. There are a number of software tools that can solve differential and algebraic equations (DAEs). These include <b>gProms</b>, <b>MATLAB</b>, <b>Modellica</b>, and others. <a href="https://apmonitor.com/compare.htm">A comparison of a gravity drained water tank model</a> is used a benchmark for these modeling languages. These software tools are very good at providing a flexible environment for DAE simulation. New users are generally impressed by the similarity to their native environments, the open-equation format, and performance gains for large-scale model simulation and optimization.</p>
<p>Experienced <b>AIMMS</b>, <b>AMPL</b>, <b>GAMS</b>, <b>Modelica</b>, or <b>gProms</b> users will likely find the modeling language easy to learn. These tools are for solving Mixed Integer Nonlinear Programming (MINLP) problems. There are a number of software tools that can solve differential and algebraic equations (DAEs). These include <b>gProms</b>, <b>MATLAB</b>, <b>Modellica</b>, and others. <a href="https://apmonitor.com/compare.htm">A comparison of a gravity drained water tank model</a> is used a benchmark for these modeling languages. These software tools are very good at providing a flexible environment for DAE simulation. New users are generally impressed by the similarity to their native environments, the open-equation format, and performance gains for large-scale model simulation and optimization.</p>
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