Overview
- Contains a detailed manual to assist with modules and test functions
- Features new updates for a local search algorithm
- Presents an efficiency comparison to earlier implementations
Part of the book series: SpringerBriefs in Optimization (BRIEFSOPTI)
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Table of contents (5 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This book explores the updated version of the GLOBAL algorithm which contains improvements for a local search algorithm and new Java implementations. Efficiency comparisons to earlier versions and on the increased speed achieved by the parallelization, are detailed. Examples are provided for students as well as researchers and practitioners in optimization, operations research, and mathematics to compose their own scripts with ease. A GLOBAL manual is presented in the appendix to assist new users with modules and test functions.
GLOBAL is a successful stochastic multistart global optimization algorithm that has passed several computational tests, and is efficient and reliable for small to medium dimensional global optimization problems. The algorithm uses clustering to ensure efficiency and is modular in regard to the two local search methods it starts with, but it can also easily apply other local techniques. The strength of this algorithm lies in its reliability and adaptive algorithm parameters. The GLOBAL algorithm is free to download also in the earlier Fortran, C, and MATLAB implementations.
Authors and Affiliations
About the authors
Bibliographic Information
Book Title: The GLOBAL Optimization Algorithm
Book Subtitle: Newly Updated with Java Implementation and Parallelization
Authors: Balázs Bánhelyi, Tibor Csendes, Balázs Lévai, László Pál, Dániel Zombori
Series Title: SpringerBriefs in Optimization
DOI: https://doi.org/10.1007/978-3-030-02375-1
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Author(s), under exclusive licence to Springer International Publishing AG, part of Springer Nature 2018
Softcover ISBN: 978-3-030-02374-4Published: 19 December 2018
eBook ISBN: 978-3-030-02375-1Published: 10 December 2018
Series ISSN: 2190-8354
Series E-ISSN: 2191-575X
Edition Number: 1
Number of Pages: IX, 111
Number of Illustrations: 11 b/w illustrations, 10 illustrations in colour
Topics: Calculus of Variations and Optimal Control; Optimization, Mathematics of Computing, Operations Research, Management Science, Analysis