Metaheuristic Optimization Algorithms: Optimizers, Analysis, and Applications
by 作者: Laith Abualigah (Editor)
Publisher Finelybook 出版社: Morgan Kaufmann
Edition 版本: 1st
Publication Date 出版日期: 2024-05-29
Language 语言: English
pages 页数: : 250 pages
ISBN-10 书号: 0443139253
ISBN-13 书号: 9780443139253
Book Description
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.
World-renowned researchers and practitioners in Metaheuristics present the procedures and pseudocode for creating a wide range of optimization algorithms
Helps readers formulate and design the best optimization algorithms for their research goals through case studies in a variety of real-world applications
Helps readers understand the links between Metaheuristic algorithms and their application in Computational Intelligence, Machine Learning, and Deep Learning problems
Review
Presents the foundations and mathematics of Metaheuristic Optimization Algorithms through a wide range of real-world applications
From the Back Cover
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 and fields. Metaheuristic Optimization Algorithms have become indispensable tools, with applications in data analysis, text mining, classification problems, computer vision, image analysis, pattern recognition, medicine, and many others. Most complex systems problems involve a continuous flow of data which makes it impossible to manage and analyze manually. The outcome depends on the processing of high-dimensional data, most of it irregular and unordered, present in various forms such as text, images, videos, audio, and graphics. The authors of Meta-Heuristic Optimization Algorithms provide 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, followed by the mathematical and procedural structure of the algorithm, associated pseudocode, and real-world case studies to demonstrate how each algorithm can be applied to a variety of scientific and engineering solutions.
About the Author
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 (), the Journal of Soft Computing (), and Journal of King Saud University - Computer and Information Sciences (Elsevier).
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