
Glowworm Swarm Optimization
Theory, Algorithms, and Applications
Springer (Publisher)
Published on 13. July 2018
Book
Paperback/Softback
XXVI, 248 pages
978-3-319-84694-1 (ISBN)
Description
This book provides a comprehensive account of the glowworm swarm optimization (GSO) algorithm, including details of the underlying ideas, theoretical foundations, algorithm development, various applications, and MATLAB programs for the basic GSO algorithm. It also discusses several research problems at different levels of sophistication that can be attempted by interested researchers. The generality of the GSO algorithm is evident in its application to diverse problems ranging from optimization to robotics. Examples include computation of multiple optima, annual crop planning, cooperative exploration, distributed search, multiple source localization, contaminant boundary mapping, wireless sensor networks, clustering, knapsack, numerical integration, solving fixed point equations, solving systems of nonlinear equations, and engineering design optimization. The book is a valuable resource for researchers as well as graduate and undergraduate studentsin the area of swarm intelligence and computational intelligence and working on these topics.
More details
Series
Edition
Softcover reprint of the original 1st ed. 2017
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
122 s/w Abbildungen
XXVI, 248 p. 122 illus.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 16 mm
Weight
423 gr
ISBN-13
978-3-319-84694-1 (9783319846941)
DOI
10.1007/978-3-319-51595-3
Schweitzer Classification
Other editions
Additional editions

Krishnanand N. Kaipa | Debasish Ghose
Glowworm Swarm Optimization
Theory, Algorithms, and Applications
Book
01/2017
Springer
€106.99
Shipment within 10-15 days
Content
Preface.- Acknowledgements.- 1 From Natural to Synthetic Swarms.- 2 Glowworm Swarm Optimization: Algorithm Development.- 3 Theoretical Foundations.- 4 Multimodal Function Optimization.- 5 Experiments using Physical Simulations and Real Robots.- 6 Applications to Ubiquitous Computing Environments.- 7 Pursuit of Multiple Mobile Signal Sources.- 8 GSO Applications and Extensions.