Comprehensive Metaheuristics
Algorithms and Applications
- 466 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Comprehensive Metaheuristics
Algorithms and Applications
About This Book
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
Frequently asked questions
Information
Table of contents
- Cover image
- Title page
- Table of Contents
- Copyright
- Contributors
- 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 structuresâ 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: LĂ©vy 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