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 [Sauer, 2022], in particular sub-sections 13.2.2 Steepest Descent and 13.1.3 Nelder-Mead.

• Section 13.2, Multivariate Case in Chapter 13 of [Chenney and Kincaid, 2013].

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.