CS 3414

Minimization of functions

CLASS XI

Reading: Cheney & Kincaid, (pp. 561-571 )

Motivational Example: PROTEIN FOLDING

In-class notes: The "grand challenge" of computational science: the protein folding problem.

CLASS XII

Reading: Cheney & Kincaid, (pp. 561-571 )

In-class notes: Newton's method for minimization.

CLASS XIII

Reading: Cheney & Kincaid, (pp. 561-566)

Fibonacci Search Algorithm

In-class notes.

CLASS XIV

Reading: Cheney & Kincaid, (pp. 566-568)

Golden Section Search Algorithm

In-class notes.

CLASS XV

Reading: Cheney & Kincaid, (pp. 573-586)

The multi-variable case.

You are not expected to understand details of methods for the multi-variable case. But you need to know that some of them exist. For "steepest descent/gradient method" you need to have a qualitative idea of what that is. You need to know why the problem of finding a global minimum in many dimensions is so difficult, the "Protein Folding" lecture (above) will help.

In-class notes. Multivariable case.
Mathematica Example:

Finding minima of a function of 2 variables.