A Derivative-free Two Level Random Search Method for Unconstrained Optimization
Author:   Neculai Andrei
Publisher:   Springer Nature Switzerland AG
Edition:   1st ed. 2021
ISBN:  

9783030685164


Pages:   118
Publication Date:   01 April 2021
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Our Price $142.29 Quantity:  
Add to Cart

Share |

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


Add your own review!

Overview

Full Product Details

Author:   Neculai Andrei
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   1st ed. 2021
Weight:   0.454kg
ISBN:  

9783030685164


ISBN 10:   3030685160
Pages:   118
Publication Date:   01 April 2021
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

1. Introduction.- 2. A Derivative-free Two Level Random Search Method for Unconstrained Optimization.- 3. Convergence of the Algorithm.- 4. Numerical Results.- 5. Conclusions.- Annex A. List of Applications.- Annex B. List of Test Functions.- Annex C. Detailed Results for 30 Large-Scale Problems.- Annex D. Detailed Results for 140 Problems.

Reviews

Author Information

Neculai Andrei holds a position at the Center for Advanced Modeling and Optimization at the Academy of Romanian Scientists in Bucharest, Romania. Dr. Andrei’s areas of interest include mathematical modeling, linear programming, nonlinear optimization, high performance computing, and numerical methods in mathematical programming. In addition to this present volume, Neculai Andrei has published several books with Springer including Nonlinear Conjugate Gradient Methods for Unconstrained Optimization (2020), Continuous Nonlinear Optimization for Engineering Applications in GAMS Technology (2017), and Nonlinear Optimization Applications Using the GAMS Technology (2013).

Tab Content 6

Author Website:  

Customer Reviews

Recent Reviews

No review item found!

Add your own review!

Countries Available

All regions
Latest Reading Guide

MRG2025CC

 

Shopping Cart
Your cart is empty
 Shopping cart
Mailing List

 

Sign up now