Swarm Intelligence : Principles, Current Algorithms and Methods, Volume 1

Swarm Intelligence (SI) is one of the most important and challenging paradigms under the umbrella of computational intelligence. It focuses on the research of collective behaviours of a swarm in nature and/or social phenomenon to solve complicated and difficult problems which cannot be handled by traditional approaches. Thousands of papers are published each year presenting new algorithms, new improvements and numerous real world applications. This makes it hard for researchers and students to share their ideas with other colleagues; follow up the works from other researchers with common interests; and to follow new developments and innovative approaches. This complete and timely collection fills this gap by presenting the latest research systematically and thoroughly to provide readers with a full view of the field of swarm. Students will learn the principles and theories of typical swarm intelligence algorithms; scholars will be inspired with promising research directions; and practitioners will find suitable methods for their applications of interest along with useful instructions. Volume 1 contains 20 chapters presenting the basic principles and current algorithms and methods of well-known swarm intelligence algorithms and efficient improvements from typical particle swarm optimization (PSO), ant colony optimization (ACO) and fireworks algorithm (FWA) as well as other swarm intelligence algorithms for swarm robotics. With contributions from an international selection of leading researchers, __Swarm Intelligence__ is essential reading for engineers, researchers, professionals and practitioners with interests in swarm intelligence. The book focuses on the principle and the current approaches of swarm intelligence algorithms for presenting the latest achievements in the principle and typical algorithms in recent years. The book mainly introduces the basic principles of typical swarm intelligence algorithms and some of their efficient improvements. Specifically, it not only includes the introductions and improvements of typical PSO, ACO and typical swarm intelligence algorithm as well as swarm robotics methods; furthermore, it also includes parts of the general swarm intelligent method research until now This book presents the basic principles and current algorithms and methods of well-known swarm intelligence algorithms and efficient improvements from typical particle swarm optimisation (PSO), ant colony optimisation (ACO) and fireworks algorithm (FWA) as well as other swarm intelligence algorithms for swarm robotics. This book includes 27 chapters and presents a great number of real-world applications of swarm intelligence algorithms and related evolutionary algorithms.