Fireworks Algorithm: A Novel Swarm Intelligence Optimization Method

di Ying Tan (Autore)

Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, 2016

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.

• Autore: Ying Tan
• Editore: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
• Anno: 2016
• Rilegatura: Paperback / softback
• Pagine: 323 p.
• Dimensioni: 235 x 155 mm
• EAN: 9783662516188

Testo in English