Swarm Intelligence

<p><strong>Swarm Intelligence: Principles Advances and Applications</strong> delivers in-depth coverage of bat artificial fish swarm firefly cuckoo search flower pollination artificial bee colony wolf search and gray wolf optimization algorithms. The book begins with a brief introduction to mathematical optimization addressing basic concepts related to swarm intelligence such as randomness random walks and chaos theory. The text then:</p><ul> <li>Describes the various swarm intelligence optimization methods standardizing the variants hybridizations and algorithms whenever possible</li> <li>Discusses variants that focus more on binary discrete constrained adaptive and chaotic versions of the swarm optimizers</li> <li>Depicts real-world applications of the individual optimizers emphasizing variable selection and fitness function design</li> <li>Details the similarities differences weaknesses and strengths of each swarm optimization method</li> <li>Draws parallels between the operators and searching manners of the different algorithms</li> </ul><p><strong>Swarm Intelligence: Principles Advances and Applications </strong>presents a comprehensive treatment of modern swarm intelligence optimization methods complete with illustrative examples and an extendable MATLAB® package for feature selection in wrapper mode applied on different data sets with benchmarking using different evaluation criteria. The book provides beginners with a solid foundation of swarm intelligence fundamentals and offers experts valuable insight into new directions and hybridizations.</p>