Comprehensive Metaheuristics: Algorithms and Applications
Author: Ali Mirjalili (Editor), Amir Hossein Gandomi (Editor)
Edition 版本: 1st
Publication Date 出版日期: 2023-02-16
Language 语言: English
Print Length 页数: 466 pages
ISBN-10: 032391781X
ISBN-13: 9780323917810
Book Description
Comprehensive Metaheuristics: Algorithms and Applications presents the foundational underpinnings of metaheuristics and a broad scope of algorithms and real-world applications across a variety of research fields. The book starts with fundamentals, mathematical prerequisites, and conceptual approaches to provide readers with a solid foundation. After presenting multi-objective optimization, constrained optimization, and problem formation for metaheuristics, world-renowned authors give readers in-depth understanding of the full spectrum of algorithms and techniques. Scientists, researchers, academicians, and practitioners who are interested in optimizing a process or procedure to achieve a goal will benefit from the case studies of real-world applications from different domains.
The book takes a much-needed holistic approach, putting the most widely used metaheuristic algorithms together with an in-depth treatise on multi-disciplinary applications of metaheuristics. Each algorithm is thoroughly analyzed to observe its behavior, providing a detailed tutorial on how to solve problems using metaheuristics. New case studies and research problem statements are also discussed, which will help researchers in their application of the concepts.
- Presented by world-renowned researchers and practitioners in metaheuristics
- Includes techniques, algorithms, and applications based on real-world case studies
- Presents the methodology for formulating optimization problems for metaheuristics
- Provides readers with methods for analyzing and tuning the performance of a metaheuristic, as well as for integrating metaheuristics in other AI techniques
- Features online complementary source code from the applications and algorithms
Review
Presents the foundational underpinnings of metaheuristics and a broad scope of algorithms and real-world applications across multiple research fields
From the Back Cover
Metaheuristics are general-purpose problem-solving Artificial Intelligence techniques that can be used to solve any sort of optimization problems subject to proper configuration. Comprehensive Metaheuristics: Algorithms and Applications presents the foundational underpinnings of Metaheuristics and the broad scope of algorithms and real-world applications across a variety of research fields. The book starts with fundamentals, mathematical pre-requisites and conceptual approaches in order to provide readers with a solid foundation of understanding. After presenting multi-objective optimization, constrained optimization, and problem formation for Metaheuristics, world-renowned authors give readers in-depth understanding of the full spectrum of algorithms and techniques in the first section of the book. Algorithms and techniques covered in Part 1 include Genetic Algorithm, Particle Swarm Optimization, Krill Herd Algorithm, Cuckoo Search Algorithm, Bat Algorithm, Grey Wolf Optimizer, Salp Swarm Optimizer, Dragonfly Algorithm, Grasshopper Optimization Algorithm, Whale Optimization Algorithm, Equilibrium Optimizer, Marine Predator Algorithm, Arithmetic Optimization Algorithm, and Differential Evolution. Scientists, researchers, academicians, and practitioners who are interested in optimizing a process or procedure to achieve a goal will benefit from the case studies of real-world applications from different domains depicted in Part 2 of the book. Comprehensive Metaheuristics: Algorithms and Applications takes a much-needed holistic approach – putting the most widely used Metaheuristic algorithms together with an in-depth treatise on multi-disciplinary applications of Metaheuristics. Each algorithm is thoroughly analyzed to observe its behavior, providing a detailed tutorial on how to solve problems using Metaheuristics. New case studies and research problem statements will also be discussed, which will help researchers in their application of the concepts, algorithms, and techniques of Metaheuristics.
About the Author
Senior lecturer S. Ali Mirjalili MD, PhD, PGDipSurgAnat, PGCertCPU works in the Anatomy and Medical Imaging Department and Convenor of Science for Surgens Course, Department of Surgery at University of Auckland, Malaysia.
Dr. Amir H. Gandomi is anARC DECRA Fellow at the Faculty of Engineering andInformation Technology, University of Technology Sydney, Australia. Prior to joining UTS, Dr. Gandomi was an Assistant Professor at Stevens Institute of Technology, USA and a Distinguished Research Fellow in BEACON center, Michigan State University, USA. Dr. Gandomi has published over two hundred journal papers and seven books which collectively have been cited 19,000+ times. He has been named as one of the most influential scientific mindsand Highly Cited Researcher (top 1% publications and 0.1% researchers) for four consecutive years, 2017 to 2020. He also ranked 18th in GP bibliography among more than 12,000 researchers. He has served as associate editor, editor and guest editor in several prestigious journals such as AE of SWEVO, IEEE TBD, and IEEE IoTJ. Dr. Gandomi is active in delivering keynotes and invited talks. His research interests are global optimization andbigdata analytics using Machine Learning and evolutionary computations in particular.
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