Overview
- Presents the latest advances in Brain Storm Optimization (BSO) algorithms
- Shares new ideas and outlines future directions of development
- Presents various concepts, principles and applications of Brain Storm Optimization algorithms
Part of the book series: Adaptation, Learning, and Optimization (ALO, volume 23)
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About this book
Brain Storm Optimization (BSO) algorithms are a new kind of swarm intelligence method, which is based on the collective behavior of human beings, i.e., on the brainstorming process. Since the introduction of BSO algorithms in 2011, many studies on them have been conducted. They not only offer an optimization method, but could also be viewed as a framework of optimization techniques. The process employed in the algorithms could be simplified as a framework with two basic operations: the converging operation and the diverging operation. A “good enough” optimum could be obtained through recursive solution divergence and convergence. The resulting optimization algorithm would naturally have the capability of both convergence and divergence.
This book is primarily intended for researchers, engineers, and graduate students with an interest in BSO algorithms and their applications. The chapters cover various aspects of BSO algorithms, and collectively provide broad insights into what these algorithms have to offer. The book is ideally suited as a graduate-level textbook, whereby students may be tasked with the study of the rich variants of BSO algorithms that involves a hands-on implementation to demonstrate the utility and applicability of BSO algorithms in solving optimization problems.
This book is primarily intended for researchers, engineers, and graduate students with an interest in BSO algorithms and their applications. The chapters cover various aspects of BSO algorithms, and collectively provide broad insights into what these algorithms have to offer. The book is ideally suited as a graduate-level textbook, whereby students may be tasked with the study of the rich variants of BSO algorithms that involves a hands-on implementation to demonstrate the utility and applicability of BSO algorithms in solving optimization problems.
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Keywords
Table of contents (11 chapters)
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Front Matter
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Foundations
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Front Matter
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Methodology
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Front Matter
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Applications
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Front Matter
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Back Matter
Editors and Affiliations
Bibliographic Information
Book Title: Brain Storm Optimization Algorithms
Book Subtitle: Concepts, Principles and Applications
Editors: Shi Cheng, Yuhui Shi
Series Title: Adaptation, Learning, and Optimization
DOI: https://doi.org/10.1007/978-3-030-15070-9
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Hardcover ISBN: 978-3-030-15069-3Published: 17 June 2019
Softcover ISBN: 978-3-030-15072-3Published: 14 August 2020
eBook ISBN: 978-3-030-15070-9Published: 03 June 2019
Series ISSN: 1867-4534
Series E-ISSN: 1867-4542
Edition Number: 1
Number of Pages: XV, 299
Number of Illustrations: 50 b/w illustrations, 58 illustrations in colour