Design Optimization

Information on APMonitor, GEKKO, MATLAB, OptdesX, and Python is listed below. Assignments and projects can be completed with any software platform.

Engineering Optimization Software is a type of programming that is used to optimize the design of products and services. It helps engineers design products faster, cheaper, and more efficiently.

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Optimization software is used to identify and implement the best solution to a given engineering problem out of all potential possibilities. It can be used to optimize the design and manufacturing processes of products, as well as to reduce costs, improve performance, and better meet customer requirements. Engineering Optimization Software can also be used to identify areas of improvement and to develop and test new designs.

Engineering Tools

Engineering Optimization Software is a type of programming that is used to optimize the design of products and services. It helps engineers design products faster, cheaper, and more efficiently. This type of software is used to identify and implement the best solution to a given engineering problem out of all potential possibilities. It can be used to optimize the design and manufacturing processes of products, as well as to reduce costs, improve performance, and better meet customer requirements. Engineering Optimization Software can also be used to identify areas of improvement and to develop and test new designs.

Engineering Tools'''

Python is a high-level and general-purpose programming language and is a top choice for programmers (Google search). Part of the reason that it is a popular choice for scientists and engineers is the language versatility, online community of users, and powerful analysis packages such as Numpy and Scipy. This course uses Python 3. Python is free and open-source and is easy to install with Anaconda (IPython, Jupyter, Spyder), PyCharm, or the Python.org distributions.

(:title Optimization Software:)

(:description Optimization software for use in engineering course:)

Engineering Optimization Software is a type of programming that is used to optimize the design of products and services. It is a type of software that can help engineers design products faster, cheaper, and more efficiently. This type of software is used to identify and implement the best solution to a given engineering problem. It can be used to optimize the design and manufacturing processes of products, as well as to reduce costs, improve performance, and better meet customer requirements. Engineering Optimization Software can also be used to identify areas of improvement and to develop and test new designs.

There are many software tools available to solve optimization problems ranging from free and open-source to proprietary commercial packages. In general, students want to choose a software platform that will be both state-of-the-art and accessible long-term. Solving optimization problems requires some familiarity with a computer programming language. Some of the popular programming languages (see TIOBE index) also include capabilities for scientific computing.

Python is a high-level and general-purpose programming language and is a top choice for programmers (Google search). Part of the reason that it is a popular choice for scientists and engineers is the language versatility, online community of users, and powerful analysis packages such as Numpy and Scipy. This course uses Python 2.7 or Python 3.7. Python is free and open-source and is easy to install with Anaconda (IPython, Jupyter, Spyder), PyCharm, or the Python.org distributions.

Information on APMonitor, GEKKO, MATLAB, OptdesX, and Python is listed below. Assignments and projects can be completed with any of these software platforms.

GEKKO (Python)

The GEKKO Optimization Suite is software for 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 data reconciliation, real-time optimization, dynamic simulation, and nonlinear predictive control. GEKKO is an object-oriented python library to facilitate local execution of APMonitor. See 18 Example problems in Python GEKKO.

Python is a high-level and general-purpose programming language and is a top choice for programmers (Google search). Part of the reason that it is a popular choice for scientists and engineers is the language versatility, online community of users, and powerful analysis packages such as Numpy and Scipy. This course uses Python 2.7 or Python 3.6+. Python is free and open-source and is easy to install with Anaconda (IPython, Jupyter, Spyder), PyCharm, or the Python.org distributions. Below is a tutorial on getting started with Python with a complete installation guide for Anaconda and Python.org.

Install Anaconda (recommended)

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Install Python from Python.org

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Install Packages with pip (Command Line)

Sometimes a script uses a package that is not yet installed. Once Python is installed, a package manager such as pip or conda can be used to install, remove, or update packages.

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Below is an example on how to install APMonitor Optimization Suite from the command line (start cmd).

 pip install APMonitor

The APMonitor package name can be replaced with any available package name such as NumPy.

 pip install numpy

Install Packages with pip (Python Script)

Packages can also be managed from a Python script by attempting to load the package with try. If the import fails, the except section imports pip and installs the package.

Load and Optionally Install APMonitor Package

(:source lang=python:) try:

   from APMonitor.apm import *

except:

   import pip
   pip.main(['install','APMonitor'])
   from APMonitor.apm import *

(:sourceend:)

Load and Optionally Install NumPy Package

(:source lang=python:) try:

   import numpy as np

except:

   import pip
   pip.main(['install','numpy'])
   import numpy as np

(:sourceend:)

The APMonitor or NumPy package names can be replaced with any available package. The pip package manager connects to an online repository to retrieve the latest version of the package and install it. Sometimes a package is needed on a computer that isn't connected to the internet or the package isn't available through pip. Below is information on installing a package wheel (whl) file.

Install Package Wheels (whl) Offline

The pip package manager can also be used to install local (previously downloaded) wheel (.whl) files but dependencies may not be automatically installed if not connected to the internet. Below is an example wheel file installation for NumPy version 1.13.1 and SciPy version 0.19.1 for Python 3.6 with 64-bit Python.

 pip install numpy-1.13.1+mkl-cp36-cp36m-win_amd64.whl
 pip install scipy-0.19.1-cp36-cp36m-win_amd64.whl

Use Christoph Gohlke's whl files for Windows installations. Many of the packages depend on the Visual C++ 2015 Redistributable (x64 and x86 for CPython 3.5 and 3.6) that is available from Microsoft. After installing the Visual C++ redistributable, download and install NumPy and SciPy packages (in that order) for Python 3.6 on Windows. The downloaded wheel file names should not be changed because the wheel file name verifies compatibility with the current Python version.

There are many optimization packages that have been developed for Python with a few of them listed below:

• Pywin32 218 for Windows Δ

Python is an open-source, versatile, interpreted high-level programming language that is supported on Windows, Linux, MacOS, etc. Python is extended by a number of add-on packages for optimization, numeric analysis, and graphical analysis. The following packages are recommended for Windows users and include Python 2.7, Numpy 1.6.2, Matplotlib 1.2.0, Scipy 0.11.0, and Pyserial 2.5.

• Scipy 0.11.0 for Windows Δ
• Pyserial 2.5 for Windows Δ

Additional links:

• Comparison of Python Integrated Development Environments (IDEs)
• Python IDE with Eclipse
• Python IDE with Wingware

• MIT Open Course Ware Tutorial on Python and IDLE

Download MATLAB and Python Tutorial Files (nlp_matlab_python_tutorial.zip)

Download MATLAB and Python Tutorial Files

Download Tutorial Files

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Information on APMonitor, MATLAB, OptdesX, and Python is listed below. Assignments and projects can be completed with any of these software platforms.