Derivative-free DIRECT-type Global Optimization

Download or Read eBook Derivative-free DIRECT-type Global Optimization PDF written by Linas Stripinis and published by Springer Nature. This book was released on 2023-12-29 with total page 131 pages. Available in PDF, EPUB and Kindle.
Derivative-free DIRECT-type Global Optimization
Author :
Publisher : Springer Nature
Total Pages : 131
Release :
ISBN-10 : 9783031465376
ISBN-13 : 3031465377
Rating : 4/5 (76 Downloads)

Book Synopsis Derivative-free DIRECT-type Global Optimization by : Linas Stripinis

Book excerpt: After providing an in-depth introduction to derivative-free global optimization with various constraints, this book presents new original results from well-known experts on the subject. A primary focus of this book is the well-known class of deterministic DIRECT (DIviding RECTangle)-type algorithms. This book describes a new set of algorithms derived from newly developed partitioning, sampling, and selection approaches in the box- and generally-constrained global optimization, including extensions to multi-objective optimization. DIRECT-type optimization algorithms are discussed in terms of fundamental principles, potential, and boundaries of their applicability. The algorithms are analyzed from various perspectives to offer insight into their main features. This explains how and why they are effective at solving optimization problems. As part of this book, the authors also present several techniques for accelerating the DIRECT-type algorithms through parallelization and implementing efficient data structures by revealing the pros and cons of the design challenges involved. A collection of DIRECT-type algorithms described and analyzed in this book is available in DIRECTGO, a MATLAB toolbox on GitHub. Lastly, the authors demonstrate the performance of the algorithms for solving a wide range of global optimization problems with various constraints ranging from a few to hundreds of variables. Additionally, well-known practical problems from the literature are used to demonstrate the effectiveness of the developed algorithms. It is evident from these numerical results that the newly developed approaches are capable of solving problems with a wide variety of structures and complexity levels. Since implementations of the algorithms are publicly available, this monograph is full of examples showing how to use them and how to choose the most efficient ones, depending on the nature of the problem being solved. Therefore, many specialists, students, researchers, engineers, economists, computer scientists, operations researchers, and others will find this book interesting and helpful.


Derivative-free DIRECT-type Global Optimization Related Books

Derivative-free DIRECT-type Global Optimization
Language: en
Pages: 131
Authors: Linas Stripinis
Categories: Mathematics
Type: BOOK - Published: 2023-12-29 - Publisher: Springer Nature

DOWNLOAD EBOOK

After providing an in-depth introduction to derivative-free global optimization with various constraints, this book presents new original results from well-know
Introduction to Derivative-Free Optimization
Language: en
Pages: 276
Authors: Andrew R. Conn
Categories: Mathematics
Type: BOOK - Published: 2009-04-16 - Publisher: SIAM

DOWNLOAD EBOOK

The first contemporary comprehensive treatment of optimization without derivatives. This text explains how sampling and model techniques are used in derivative-
Numerical Computations: Theory and Algorithms
Language: en
Pages: 550
Authors: Yaroslav D. Sergeyev
Categories: Computers
Type: BOOK - Published: 2020-02-13 - Publisher: Springer Nature

DOWNLOAD EBOOK

The two-volume set LNCS 11973 and 11974 constitute revised selected papers from the Third International Conference on Numerical Computations: Theory and Algorit
Black Box Optimization, Machine Learning, and No-Free Lunch Theorems
Language: en
Pages: 388
Authors: Panos M. Pardalos
Categories: Mathematics
Type: BOOK - Published: 2021-05-27 - Publisher: Springer Nature

DOWNLOAD EBOOK

This edited volume illustrates the connections between machine learning techniques, black box optimization, and no-free lunch theorems. Each of the thirteen con
Derivative-Free and Blackbox Optimization
Language: en
Pages: 307
Authors: Charles Audet
Categories: Mathematics
Type: BOOK - Published: 2017-12-02 - Publisher: Springer

DOWNLOAD EBOOK

This book is designed as a textbook, suitable for self-learning or for teaching an upper-year university course on derivative-free and blackbox optimization. Th