Swarm Intelligence Principles, Advances, and Applications

Swarm 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 Draws parallels between the operators and searching manners of the different algorithms Swarm Intelligence: Principles, Advances, and Applications 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.

IntroductionSources of InspirationRandom VariablesPseudo-Random Number GenerationRandom WalkChaosChapter ConclusionBibliography Bat AlgorithmBat Algorithm (BA)BA VariantsBat HybridizationsBA in Real-World ApplicationsChapter ConclusionBibliography Artificial Fish Swarm AlgorithmFish Swarm OptimizationArtificial Fish Swarm Algorithm (AFSA) VariantsAFSA HybridizationsFish Swarm in Real-World ApplicationsChapter ConclusionBibliography Cuckoo Search AlgorithmCuckoo Search (CS)CS VariantsCS HybridizationsCS in Real-World ApplicationsChapter ConclusionBibliography Firefly AlgorithmFirefly Algorithm (FFA)FFA VariantFFA HybridizationsFirefly in Real-World ApplicationsChapter ConclusionBibliography Flower Pollination AlgorithmFlower Pollination Algorithm (FPA)FPA VariantsFPA: HybridizationsReal-World Applications of the FPAFPA in Feature SelectionChapter ConclusionBibliography Artificial Bee Colony OptimizationArtificial Bee Colony (ABC)ABC VariantsABC HybridizationsABC in Real-World ApplicationsChapter ConclusionBibliography Wolf-Based Search AlgorithmsWolf Search Algorithm (WSA)Wolf Search Optimizers in Real-World ApplicationsChapter ConclusionBibliography Bird's-Eye ViewCriteria (1) Classification According to Swarm GuideCriteria (2) Classification According to the Probability Distribution UsedCriteria (3) Classification According to the Number of Behaviors UsedCriteria (4) Classification According to Exploitation of Positional Distribution of AgentsCriteria (5) Number of Control ParametersCriteria (6) Classification According to Either Generation of Completely New Agents per IterationCriteria (7) Classification Based on Exploitation of Velocity Concept in the OptimizationCriteria (8) Classification According to the Type of Exploration/Exploitation UsedChapter Conclusion

Aboul Ella Hassanien is a full professor in the Information Technology Department of the Faculty of Computers and Information at Cairo University, Giza, Egypt. Widely published and highly decorated, he is the founder and chair of the Scientific Research Group in Egypt, has established the Egyptian Rough Sets Society, and is chairing the Egyptian International Rough Set Society Chapter. He has served as a general chair, co-chair, program chair, and program committee member of various international conferences, and as a reviewer and guest editor for numerous international journals. His research interests include computational intelligence, network security, animal identification, and more. Eid Emary is currently a lecturer in the Information Technology Department of the Faculty of Computers and Information at Cairo University, Giza, Egypt. He has authored or co-authored more than 15 research publications in peer-reviewed journals, book chapters, and conference proceedings. He has served as a technical program committee member of various international conferences, and as a reviewer for numerous international journals. His research interests are in the areas of computer vision, mathematical optimization, pattern recognition, video and image processing, machine learning, data mining, and biometrics.