Comprehensive Metaheuristics: Algorithms and Applications - Tapa blanda

Acerca de los autores

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.

De la contraportada

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.