Metaheuristic Optimization Algorithms Optimizers, Analysis, and Applications

Metaheuristic Optimization Algorithms: Optimizers, Analysis, and Applications presents the most recent optimization algorithms and their applications across a wide range of scientific and engineering research fields. The book provides readers with a comprehensive overview of eighteen optimization algorithms to address this complex data, including Particle Swarm Optimization Algorithm, Arithmetic Optimization Algorithm, Whale Optimization Algorithm, and Marine Predators Algorithm, along with new and emerging methods such as Aquila Optimizer, Quantum Approximate Optimization Algorithm, Manta-Ray Foraging Optimization Algorithm, and Gradient Based Optimizer, among others. Each chapter includes an introduction to the modeling concepts used to create the algorithm that is followed by the mathematical and procedural structure of the algorithm, associated pseudocode, and real-world case studies.

1. Particle Swarm Optimization Algorithm: Analysis and Applications
2. Social spider optimization algorithm: Analysis and Applications
3. Animal Migration Optimization Algorithm: Analysis And Applications
4. Cuckoo Search Algorithm: Analysis and Applications
5. Teaching Learning Based Optimization Algorithm: Analysis and Applications
6. Arithmetic Optimization Algorithm: Analysis and Applications
7. Aquila Optimizer: Algorithm, Analysis, and Applications
8. Whale Optimization Algorithm: Analysis and Applications
9. Spider Monkey Optimization Algorithm: Analysis and Applications
10. Marine Predators Algorithm: Analysis and Applications
11. Quantum Approximate Optimization Algorithm: Analysis and Applications
12. Crow Search Algorithm: Analysis and Applications
13. Henry Gas Solubility Optimization Algorithm: Analysis and Applications
14. Manta-Ray Foraging Optimization: Algorithm, Analysis, and Applications
15. Moth-flame Optimization Algorithm: Analysis and Applications
16. Gradient Based Optimizer: Analysis and Application of Berry Soft-ware Product
17. Krill Herd (KH) Algorithm: Analysis and Applications
18. Salp Swarm Algorithm: Optimization, Analysis, and Applications

Dr. Laith Abualigah is an Associate Professor at Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Jordan. He is also a distinguished researcher at the School of Computer Science, Universiti Sains Malaysia. His main research interests focus on Arithmetic Optimization Algorithms (AOA), Bio-inspired Computing, Nature-inspired Computing, Swarm Intelligence, Artificial Intelligence, Meta-heuristic Modeling, as well as Optimization Algorithms, Evolutionary Computations, Information Retrieval, Text Clustering, Feature Selection, Combinatorial Problems, Optimization, Advanced Machine Learning, Big Data, and Natural Language Processing. Dr. Abualigah currently serves as Associate Editor of the Journal of Cluster Computing (Springer), the Journal of Soft Computing (Springer), and Journal of King Saud University - Computer and Information Sciences (Elsevier).