About this document
Unconstrained Optimization in Multiple Variables by slv_prasaad is a document available to read on EtoBox.
This document discusses unconstrained optimization of functions with multiple variables. It provides that the necessary condition for a stationary point is for the gradient vector to be equal to zero. The sufficient condition for a stationary point to be a minimum is for the Hessian matrix to be positive definite, while for a maximum the Hessian must be negative definite. An example problem is worked through to find the stationary points and classify them as maxima or minima based on the Hessian.
- Author
- slv_prasaad
- Language
- EN