Skip to content

Paulnkk/Nonlinear-Optimization-Algorithms

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Nonlinear Optimization Algorithms

During my time as Scientific Assistant at the Karlsruhe Institute of Technology (Germany) I implemented various standard Optimization Algorithms solving unrestricted nonlinear Problems; Gradient-Descent-Method, Newton-Method, Conjugate-Gradient-Descent-Method, BFGS-Method and a Trust-Region-Method in Python.

In addition, I implemented an Armijo linesearch.

The code is implemented in an object-oriented manner, whereby each method is implemented in a class (bfgs.py, cg.py, gradv.py, newtonm.py and tr.py) and executed via the ros_test.py script. In the script ros_test.py the Rosenbrock function was implemented, which is minimized to a given starting point x_0 with each method.

Releases

No releases published

Packages

No packages published

Languages

pFad - Phonifier reborn

Pfad - The Proxy pFad of © 2024 Garber Painting. All rights reserved.

Note: This service is not intended for secure transactions such as banking, social media, email, or purchasing. Use at your own risk. We assume no liability whatsoever for broken pages.


Alternative Proxies:

Alternative Proxy

pFad Proxy

pFad v3 Proxy

pFad v4 Proxy