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Comprehensive Metaheuristics: Algorithms and Applications

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Comprehensive Metaheuristics: Algorithms and ApplicationsНазвание: Comprehensive Metaheuristics: Algorithms and Applications
Автор: Seyedali Mirjalili, Amir H. Gandomi
Издательство: Academic Press/Elsevier
Год: 2023
Страниц: 468
Язык: английский
Формат: pdf (true)
Размер: 22.0 MB

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.

Contents:
Chapter 1: Chaos theory in metaheuristics
Chapter 2: Metaheuristic approaches for solving multiobjective optimization problems
Chapter 3: A brief overview of physics-inspired metaheuristics
Chapter 4: Evolutionary computation techniques for optimal response actions against water distribution networks contamination
Chapter 5: Metaheuristic technique for solving fuzzy nonlinear equations
Chapter 6: Metaheuristic algorithms in network intrusion detection
Chapter 7: Metaheuristic algorithms in text clustering
Chapter 8: Application of metaheuristic algorithms in optimal design of sewer collection systems
Chapter 9: Space truss structures’ optimization using metaheuristic optimization algorithms
Chapter 10: Metaheuristics for solving the wind turbine placement problem
Chapter 11: Use of metaheuristics in industrial development and their future perspectives
Chapter 12: Levy flight and Chaos theory based metaheuristics for grayscale image thresholding
Chapter 13: Metaheuristics for optimal feature selection in high-dimensional datasets
Chapter 14: Optimal deployment of sensors for leakage detection in water distribution systems using metaheuristics
Chapter 15: Metaheuristic-based automatic generation controller in interconnected power systems with renewable energy sources
Chapter 16: Route optimization in MANET using swarm intelligence algorithm
Chapter 17: The promise of metaheuristic algorithms for efficient operation of a highly complex power system
Chapter 18: Genome sequence assembly using metaheuristics
Chapter 19: Metaheuristics for optimizing weights in neural networks
Chapter 20: Metaheuristics for clustering problems
Chapter 21: Employment of bio-inspired algorithms in the field of antenna array optimization: A review
Chapter 22: Foundations of combinatorial optimization, heuristics, and metaheuristics
Index

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