Comprehensive Metaheuristics: Algorithms and Applications

ISBN 10: 032391781X / ISBN 13: 9780323917810

Editore: Elsevier Science & Technology, 2023

Riguardo questo articolo

Inhaltsverzeichnisrnrn1. Chaos theory in metaheuristcs 2. A New Metaheuristic Approach for Solving Multi-Objective Optimization Problems 3. A Brief Overview of Physics-inspired Metaheuristic Optimization Techniques 4. App.

Codice articolo 607782689

Dati bibliografici

• Titolo: Comprehensive Metaheuristics: Algorithms and Applications
• Editore: Elsevier Science & Technology
• Data di pubblicazione: 2023
• Lingua: Inglese
• ISBN 10: 032391781X
• ISBN 13: 9780323917810
• Rilegatura: Kartoniert / Broschiert
• Condizione: New

Descrizione articolo

Riassunto

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

Informazioni sugli autori

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.

Amir H. Gandomi, PhD, is a leading researcher in global optimization and big data analytics, currently serving as a Professor of Data Science and an ARC DECRA Fellow at the University of Technology Sydney (UTS). With over 450 journal publications and 60,000 citations, he is among the most cited researchers worldwide. Dr. Gandomi has authored 14 books and received numerous accolades, including the IEEE TCSC Award and the Achenbach Medal. His editorial roles span several prestigious journals, and he is a sought-after keynote speaker in the fields of artificial intelligence and genetic programming. Previously, he held academic positions at the Stevens Institute of Technology and Michigan State University, where he contributed significantly to advancing knowledge in machine learning and evolutionary computation.