Swarm Intelligence: Principles, Advances, and Applications

Hassanien, A. E., and E. Alamry, Swarm Intelligence: Principles, Advances, and Applications, , New yourk, CRC – Taylor & Francis Group, 2015.


warm Intelligence: Principles, Advances, and Applications 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: Describes the various swarm intelligence optimization methods, standardizing the variants, hybridizations, and algorithms whenever possible
Discusses variants that focus more on binary, discrete, constrained, adaptive, and chaotic versions of the swarm optimizers, Depicts real-world applications of the individual optimizers, emphasizing variable selection and fitness function design, Details the similarities, differences, weaknesses, and strengths of each swarm optimization method and Draws parallels between the operators and searching manners of the different algorithms

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