Overview
- Reviews the state-of-the-art of firework algorithms (FWA) as a novel explosive search way for optimization
- Offers the key operators and characteristics as well as theoretical analyses of convergence and time-complexity of FWA through stochastic Markov process
- Presents exhaustively the key recent research into varieties of improving versions of FWA so far
- Enriches understanding of FWA by incorporating FWA with GPU, MOO, and combinatorial optimization
- Covers many different applications including NMF, document clustering, pattern recognition, inversion problem, and swarm robotics
- Includes supplementary material: sn.pub/extras
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About this book
This book is devoted to the state-of-the-art in all aspects of fireworks algorithm (FWA), with particular emphasis on the efficient improved versions of FWA. It describes the most substantial theoretical analysis including basic principle and implementation of FWA and modeling and theoretical analysis of FWA. It covers exhaustively the key recent significant research into the improvements of FWA so far. In addition, the book describes a few advanced topics in the research of FWA, including multi-objective optimization (MOO), discrete FWA (DFWA) for combinatorial optimization, and GPU-based FWA for parallel implementation. In sequels, several successful applications of FWA on non-negative matrix factorization (NMF), text clustering, pattern recognition, and seismic inversion problem, and swarm robotics, are illustrated in details, which might shed new light on more real-world applications in future. Addressing a multidisciplinary topic, it will appeal to researchers and professionals in the areas of metahuristics, swarm intelligence, evolutionary computation, complex optimization solving, etc.
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Keywords
Table of contents (17 chapters)
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Front Matter
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Fundamentals and Basic Theory
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Front Matter
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Applications
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Front Matter
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Authors and Affiliations
Bibliographic Information
Book Title: Fireworks Algorithm
Book Subtitle: A Novel Swarm Intelligence Optimization Method
Authors: Ying Tan
DOI: https://doi.org/10.1007/978-3-662-46353-6
Publisher: Springer Berlin, Heidelberg
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2015
Hardcover ISBN: 978-3-662-46352-9Published: 20 October 2015
Softcover ISBN: 978-3-662-51618-8Published: 23 August 2016
eBook ISBN: 978-3-662-46353-6Published: 11 October 2015
Edition Number: 1
Number of Pages: XXXIX, 323
Topics: Artificial Intelligence, Computational Intelligence, Numeric Computing, Robotics and Automation