Quasi Newton Methods in Optimization

Quasi-Newton Approximations

The following exercise demonstrates the use of Quasi-Newton methods, Newton's methods, and a Steepest Descent approach to unconstrained optimization. The following tutorial covers:

  • Newton's method (exact 2nd derivatives)
  • BFGS-Update method (approximate 2nd derivatives)
  • Conjugate gradient method
  • Steepest descent method

Search Direction Homework

Chapter 3 covers each of these methods and the theoretical background for each. The following exercise is a practical implementation of each method with simplified example code for instructional purposes. The examples do not perform line searching which will be covered in more detail later.

MATLAB Source Code

Python Source Code

This assignment can be completed in groups of two. Additional guidelines on individual, collaborative, and group assignments are provided under the Expectations link.