From nature, we observe swarming behavior in the form of ant colonies, bird flocking, animal herding, honey bees, swarming of bacteria, and many more. It is only in recent years that researchers have taken notice of such natural swarming systems as culmination of some form of innate collective intelligence, albeit swarm intelligence (SI) - a metaphor that inspires a myriad of computational problem-solving techniques. In computational intelligence, swarm-like algorithms have been successfully applied to solve many real-world problems in engineering and sciences. This handbook volume serves as a useful foundational as well as consolidatory state-of-art collection of articles in the field from various researchers around the globe. It has a rich collection of contributions pertaining to the theoretical and empirical study of single and multi-objective variants of swarm intelligence based algorithms like particle swarm optimization (PSO), ant colony optimization (ACO), bacterial foraging optimization algorithm (BFOA), honey bee social foraging algorithms, and harmony search (HS). With chapters describing various applications of SI techniques in real-world engineering problems, this handbook can be a valuable resource for researchers and practitioners, giving an in-depth flavor of what SI is capable of achieving.
... Business; Publisher: IGI Global, Hershey, USA. He was the member of the Young Researchers' Committee of the WSC 2008 Online World Conference on Soft Computing in Industrial Applications. He ... computer science and 730 About the Contributors.
This book is ideally designed for IT specialists, researchers, academicians, engineers, developers, practitioners, and students seeking current research on the real-world applications of intelligent algorithms.
... authored 13 books , including “ Fireworks Algorithm ” by Springer in 2015 , and “ GPU - based Parallel Implementation of Swarm Intelligence Algorithms ” by Morgan Kaufmann ( Elsevier ) in 2016 , and received 5 invention patents .
The movement of people in buildings and design solutions for means of egress. Fire Technology, 20(1), 27–47. doi:10.1007/ BF02390046 Pelechano, N., Allbeck, J. M., & Badler, N. I. (2007). 170 PHuNAC Model.
Handbook of Particle Swarm Optimization: Concepts, Principles and Applications
The Handbook of Research on Soft Computing and Nature-Inspired Algorithms is an essential source for the latest scholarly research on applications of nature-inspired computing and soft computational systems.
893-897). Academic Press. doi:10.1109/ICDAR.2005.53 Elloumi, M., & Zomaya, A. Y. (2014). Biological Knowledge Discovery Handbook: Preprocessing, Mining and Postprocessing of Biological Data. John Wiley. Elmannoubi, M., Tebourbi ...
... suit is excluded by the proposers due to its unstable behavior . We optimized these functions of four dimensions D ( 10D , 30D , 50D , and 100D ) . The initial populations are generated uniformly random in the search space . All ...
The implemented controller is then plugged into the TORCS racing environment and is involved in a 3D racing game. During the race, the cultural algorithm is utilized to learn the social context to optimize the controller's state handler ...
The book provides beginners with a solid foundation of swarm intelligence fundamentals, and offers experts valuable insight into new directions and hybridizations.