Swarm Intelligence (SI) has grown significantly, both from the perspective of algorithmic development and applications covering almost all disciplines science and technology. This book emphasizes the studies of existing SI techniques, their variants and applications. The book also contains reviews of new developments in SI techniques and hybridizations. Algorithm specific studies covering basic introduction and analysis of key components of these algorithms, such as convergence, balance of solution accuracy, computational costs, tuning and control of parameters. Application specific studies incorporating the ways of designing objective functions, solution representation and constraint handling. The book also includes studies on application domain specific adaptations in the SI techniques. The book will be beneficial for academicians and researchers from various disciplines of engineering and science working in applications of SI and other optimization problems.

Focuses on the studies of existing Swarm Intelligence techniques, their variants and applications Presents studies covering basic introduction and analysis of key components of the algorithms Presents applications incorporating the ways of designing objective functions and solution representation

Inhalt
A Brief Tutorial on Optimization Problems, Optimization Algorithms, Meta-heuristics, and Swarm Intelligence.- Introductory Review of Swarm Intelligence Techniques.- Swarm Intelligence for Deep Learning: Concepts, Challenges and Recent Trends.- Advances on Particle Swarm Optimization in Solving Discrete Optimization Problems.- Performance Analysis of Hybrid Memory Based Dragonfly Algorithm in Engineering Problems.