## Python Optimization Package

## Main.PythonApp History

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python pip install gekko

Instructions below are for working with the original APM Python package that requires an APM model and data files. The advantage of working with GEKKO is that the model equations and data are defined directly within the Python language instead of in separate files (see documentation).

**Recommended:** A newer Python interface is the GEKKO Optimization Suite that is available with:

python pip install gekko

Instructions below are for working with the original APM Python package that requires an APM model and data files. The advantage of working with GEKKO is that the model equations and data are defined directly within the Python language instead of in separate files (see documentation). There is also an option to run locally in GEKKO without an Apache server for Linux and Windows. Both APM Python and GEKKO solve optimization problems on public servers by default and this option is available for all platforms (Windows, Linux, MacOS, ARM processors, etc) that run Python.

python pip install gekko

Instructions below are for working with the original APM Python package that requires an APM model and data files. The advantage of working with GEKKO is that the model equations and data are defined directly within the Python language instead of in separate files (see documentation).

Another method to obtain APMonitor is to include the following code snippet at the beginning of a Python script. If APMonitor is not available, it will use the pip module to install it.

try: from APMonitor.apm import * except: # Automatically install APMonitor import pip pip.main(['install','APMonitor']) from APMonitor.apm import *

Another method to obtain APMonitor is to include the following code snippet at the beginning of a Python script. The installation is only required once and then the code can be commented or removed.

(:source lang=python:) try:

from pip import main as pipmain

except:

from pip._internal import main as pipmain

pipmain(['install','APMonitor'])

- to upgrade: pipmain(['install','--upgrade','APMonitor'])

(:sourceend:)

The Dynamic Optimization Course is graduate level course taught over 14 weeks to introduce concepts in mathematical modeling, data reconciliation, estimation, and control. There are many other applications and instructional material posted to this freely available course web-site.

from apm import *

from APMonitor.apm import *

from apm import *

from APMonitor.apm import *

from APMonitor import *

from apm import *

from APMonitor import *

from apm import *

(:html:) <iframe width="560" height="315" src="https://www.youtube.com/embed/WF3iieZfRA0" frameborder="0" allowfullscreen></iframe> (:htmlend:)

Example applications of nonlinear models with differential and algebraic equations are available for download below or from the following GitHub repository.

(:html:) <iframe width="560" height="315" src="https://www.youtube.com/embed/t84YMw8p34w?rel=0" frameborder="0" allowfullscreen></iframe> (:htmlend:)

The development roadmap for this and other libraries are detailed in the release notes. The zipped archive contains the APM Python library **apm.py** and a number of example problems in separate folders. Descriptions of the example problems are provided below.

The development roadmap for this and other libraries are detailed in the release notes. The zipped archive contains the APM Python library **apm.py** and a number of example problems in separate folders. Descriptions of some of the example problems are provided below.

(:source lang=python:) try:

Another method to obtain APMonitor is to include the following code snippet at the beginning of a Python script. If APMonitor is not available, it will use the pip module to install it.

try:

except:

except:

def install(package): pip.main(['install', package]) # Example if __name__ ==_{_main_}: install('APMonitor')

pip.main(['install','APMonitor'])

(:sourceend:)

(:source lang=python:) try:

from APMonitor import *

except:

# Automatically install APMonitor import pip def install(package): pip.main(['install', package]) # Example if __name__ ==_{_main_}: install('APMonitor') from APMonitor import *

(:sourceend:)

$$ s.t. x_1 x_2 x_3 x_4 \ge 25$$

$$ \mathrm{subject\;to} \quad x_1 x_2 x_3 x_4 \ge 25$$

$$ s.t. x_1 x_2 x_3 x_4 /ge 25$$

$$ x_1^2 + x_2^2 + x_3^2 + x_4^2 = 40$$

$$ 1 \le x_1, x_2, x_3, x_4 \le 5$$

$$ x_0 = (1,5,5,1)$$

$$ s.t. x_1 x_2 x_3 x_4 \ge 25$$

$$\quad x_1^2 + x_2^2 + x_3^2 + x_4^2 = 40$$

$$\quad 1 \le x_1, x_2, x_3, x_4 \le 5$$

$$\quad x_0 = (1,5,5,1)$$

$$ \min \, x_1 x_4 (x_1 + x_2 + x_3) + x_3 $$

$$ \min x_1 x_4 (x_1 + x_2 + x_3) + x_3 $$ $$ s.t. x_1 x_2 x_3 x_4 /ge 25$$ $$ x_1^2 + x_2^2 + x_3^2 + x_4^2 = 40$$ $$ 1 \le x_1, x_2, x_3, x_4 \le 5$$

$$ x_0 = (1,5,5,1)$$

$$ /min /, x_1 x_4 \left(x_1 + x_2 + x_3 \right) + x_3 $$

$$ \min \, x_1 x_4 (x_1 + x_2 + x_3) + x_3 $$

$$ /min /, x_1 x_4 \left(x_1 + x_2 + x_3 \right) + x_3 $$

The APMonitor package is also available through the package manager **pip** in Python.

python pip install APMonitor

The latest APM Python libraries are attached below. Functionality has been tested with Python 2.7. Example applications that use the apm.py library are listed further down on this page.

The latest APM Python libraries are attached below. Functionality has been tested with Python 2.7 and 3.5. Example applications that use the apm.py library are listed further down on this page.

## APM Python

- APM IPython Notebook Example on GitHub

(:title Nonlinear Optimization with Python:)

(:title Python Optimization Package:)

Solve this problem problem from a web-browser interface.

- Solve this optimization problem from a web-browser interface or download the Python source above. The Python files are contained in folder
*example_hs71*.

Hock-Schittkowsky Test Suite #71

Solve this problem problem from a web-browser interface.

(:html:) <iframe width="560" height="315" src="https://www.youtube.com/embed/t84YMw8p34w?rel=0" frameborder="0" allowfullscreen></iframe> (:htmlend:)