Overview
- Contains a survey on Lipschitz deterministic global optimization methods
- Outlines a new class of algorithms
- Maximizes reader insights into multiextremal continuous problems
- Includes case studies
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Optimization (BRIEFSOPTI)
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Table of contents (4 chapters)
Reviews
“The topic of the book and the class of algorithms described in the volume are of an indisputable interest … . the book under review gives an important contribution to the existing optimization literature. It will be interesting to a broad scientific community working with application and development of global optimization algorithms. Engineers, researchers, and students will find this volume extremely useful and inspiring.” (Timoleon Kipouros, Journal of Global Optimization, Vol. 80, 2021)
“The book is well-organized, self-contained, and technically sound. I think it will be highly requested not only by researchers in the field of global (and local) optimization but also by engineers, graduate and postgraduate students, and practitioners.” (Antanas Zilinskas, Optimization Letters, Vol. 15, 2021)
“The authors of this brief book consider global optimization problems, in which the Lipschitz continuity condition is satisfied. … This book will be for sure interesting for the researchers and PhD students working in the area of global optimization.” (Marcin Anholcer, zbMATH 1371.90112, 2017)
Authors and Affiliations
About the authors
Dmitri Kvasov is an Assistant Professor at DIMES, University of Calabria, Rende,Italy and Senior Programmer at the Institute of Information Technology, Mathematics and Mechanics at Lobachevsky State University of Nizhny Novgorod, Russia. His research interest includes numerical analysis, continuous global optimization, and infinity computing.
Bibliographic Information
Book Title: Deterministic Global Optimization
Book Subtitle: An Introduction to the Diagonal Approach
Authors: Yaroslav D. Sergeyev, Dmitri E. Kvasov
Series Title: SpringerBriefs in Optimization
DOI: https://doi.org/10.1007/978-1-4939-7199-2
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Author(s) 2017
Softcover ISBN: 978-1-4939-7197-8Published: 18 June 2017
eBook ISBN: 978-1-4939-7199-2Published: 16 June 2017
Series ISSN: 2190-8354
Series E-ISSN: 2191-575X
Edition Number: 1
Number of Pages: X, 136
Number of Illustrations: 39 b/w illustrations
Topics: Programming Techniques, Optimization, Mathematics of Computing, Mathematical Applications in Computer Science