An optimization toolbox with visualizations
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Interactive Optimization Toolbox
Developed by Shahrokh Shahi
Georgia Institute of Technology
2018-2019
About
This tool includes an implementation of five gradient-based algorithms, including
- (1) Steepest Descend Algorithm (SDA),
- (2) Conjugate Gradient Algorithm (CGA),
- (3) Newton's Method,
- (4) Davidson-Fletcher-Powell (DFP) Method,
- (5) Broyden–Fletcher–Goldfarb–Shanno (BFGS) Method,
for multivariate function optimization. For two variable functions, a user-friendly interactive interface is available which portrays the optimization procedure step-by-step. This toolbox can also serve as an educational tool to understand mainstream optimization techniques.
Details
- For more information about the details, see my blog post.
Sample run
- An animation of the toolbox
Install the toolbox on MATLAB
- Run "OPTool.mltbx" in MATLAB and complete the installation
- Run OPTool in MATLAB command window
- Enjoy! (the app will be run with a pre-set values as an example)
Please note that the GUI is built and tested in Windows; there might be some visuall diferences in macOS (for instance, the test may appear smaller)
Zitieren als
shahrokh shahi (2026). OPTool (https://github.com/shahrokhx/Interactive_Optimization_Toolbox/releases/tag/v4.1), GitHub. Abgerufen .
Allgemeine Informationen
- Version 4.1 (6,54 MB)
-
Lizenz auf GitHub anzeigen
Kompatibilität der MATLAB-Version
- Kompatibel mit allen Versionen
Plattform-Kompatibilität
- Windows
- macOS
- Linux
| Version | Veröffentlicht | Versionshinweise | Action |
|---|---|---|---|
| 4.1 |
|

