Can I read A Derivative-free Two Level Random Search Method for Unconstrained Optimization on EtoBox?

A Derivative-free Two Level Random Search Method for Unconstrained Optimization by Neculai Andrei is a nonfiction available to read on EtoBox.

What is A Derivative-free Two Level Random Search Method for Unconstrained Optimization about?

The book is intended for graduate students and researchers in mathematics, computer science, and operational research. The book presents a new derivative-free optimization method/algorithm based on randomly generated trial points in specified domains and where the best ones are selected at each iteration by using a number of rules. This method is different from many other well established methods presented in the literature and proves to be competitive for solving many unconstrained optimization problems with different structures and complexities, with a relative large number of variables. Intensive numerical experiments with 140 unconstrained optimization problems, with up to 500 variables, have shown that this approach is efficient and robust. Structured into 4 chapters, Chapter 1 is introductory. Chapter 2 is dedicated to presenting a two level derivative-free random search method for unconstrained optimization. It is assumed that the minimizing function is continuous, lower bounded and its minimum value is known. Chapter 3 proves the convergence of the algorithm. In Chapter 4, the numerical performances of the algorithm are shown for solving 140 unconstrained optimization probl

Who reads A Derivative-free Two Level Random Search Method for Unconstrained Optimization?

Author

Neculai Andrei

Publisher

Springer International Publishing : Imprint: Springer

Published

2021

Language

EN

ISBN

9783030685188

Category

nonfiction

Subjects

Mathematics, Science, Business