Algoritmus využívající kvadratické interpolace pro minimalizaci funkce bez omezení

Abstract

This work is devoted to methods for unconstrained minimization. Classical methods need the knowledge of first derivation (gradient) eventually second derivation (Hessian). However, if both of these numbers are hard to evaluate, we use derivative free algorithms. An algorithm using quadratic interpolation for unconstrained optimization is one of them. The goal of this work is to describe the basics features of this method, to cover the whole algorithm and then to implement the code of program.