5.2. Finding the Minimum of a Function of Several Variables — Coming Soon

Last Revised on October 12, 2024 (for typos)

References:

• Chapter 13, Optimization, of [Sau22], Sub-sections 13.2.2, Steepest Descent, and 13.1.3, Nelder-Mead.

• Section 13.2, Multivariate Case, of [CK13].

5.2.1. Introduction

This future section will focus on two methods for computing the minimum (and its location) of a function \(f(x, y, \dots)\) of several variables:

• Steepest Descent where the gradient is used iteratively to find the direction in which to search for a new approximate location where \(f\) has a lower value.

• The method of Nelder and Mead, which does not use derivatives.