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.
1. Comprehensive Metaheuristics - p. iii 2. Cover - p. iii 3. Title Page - p. iii 4. Copyright Page - p. iv 5. Table of Contents - p. iv 6. Contributors - p. xvii 7. Chapter 1 Chaos theory in metaheuristics - p. 1 8. Chapter 2 Metaheuristic approaches for solving multiobjective optimization problems - p. 21 9. Chapter 3 A brief overview of physics-inspired metaheuristics - p. 49 10. Chapter 4 Evolutionary computation techniques for optimal response actions against water distribution networks contamination - p. 65 11. Chapter 5 Metaheuristic technique for solving fuzzy nonlinear equations - p. 85 12. Chapter 6 Metaheuristic algorithms in network intrusion detection - p. 95 13. Chapter 7 Metaheuristic algorithms in text clustering - p. 131 14. Chapter 8 Application of metaheuristic algorithms in optimal design of sewer collection systems - p. 153 15. Chapter 9 Space truss structures’ optimization using metaheuristic optimization algorithms - p. 163 16. Chapter 10 Metaheuristics for solving the wind turbine placement problem - p. 181 17. Chapter 11 Use of metaheuristics in industrial development and their future perspectives - p. 195 18. Chapter 12 Lévy flight and Chaos theory based metaheuristics for grayscale image thresholding - p. 203 19. Chapter 13 Metaheuristics for optimal feature selection in high-dimensional datasets - p. 237 20. Chapter 14 Optimal deployment of sensors for leakage detection in water distribution systems using metaheuristics - p. 269 21. Chapter 15 Metaheuristic-based automatic generation controller in interconnected power systems with renewable energy sources - p. 293 22. Chapter 16 Route optimization in MANET using swarm intelligence algorithm - p. 313 23. Chapter 17 The promise of metaheuristic algorithms for efficient operation of a highly complex power system - p. 325 24. Chapter 18 Genome sequence assembly using metaheuristics - p. 347 25. Chapter 19 Metaheuristics for optimizing weights in neural networks - p. 359 26. Chapter 20 Metaheuristics for clustering problems - p. 379 27. Chapter 21 Employment of bio-inspired algorithms in the field of antenna array optimization: A review - p. 393 28. Chapter 22 Foundations of combinatorial optimization, heuristics, and metaheuristics - p. 407 29. Index - p. 439
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.
1. Comprehensive Metaheuristics - p. iii 2. Cover - p. iii 3. Title Page - p. iii 4. Copyright Page - p. iv 5. Table of Contents - p. iv 6. Contributors - p. xvii 7. Chapter 1 Chaos theory in metaheuristics - p. 1 8. Chapter 2 Metaheuristic approaches for solving multiobjective optimization problems - p. 21 9. Chapter 3 A brief overview of physics-inspired metaheuristics - p. 49 10. Chapter 4 Evolutionary computation techniques for optimal response actions against water distribution networks contamination - p. 65 11. Chapter 5 Metaheuristic technique for solving fuzzy nonlinear equations - p. 85 12. Chapter 6 Metaheuristic algorithms in network intrusion detection - p. 95 13. Chapter 7 Metaheuristic algorithms in text clustering - p. 131 14. Chapter 8 Application of metaheuristic algorithms in optimal design of sewer collection systems - p. 153 15. Chapter 9 Space truss structures’ optimization using metaheuristic optimization algorithms - p. 163 16. Chapter 10 Metaheuristics for solving the wind turbine placement problem - p. 181 17. Chapter 11 Use of metaheuristics in industrial development and their future perspectives - p. 195 18. Chapter 12 Lévy flight and Chaos theory based metaheuristics for grayscale image thresholding - p. 203 19. Chapter 13 Metaheuristics for optimal feature selection in high-dimensional datasets - p. 237 20. Chapter 14 Optimal deployment of sensors for leakage detection in water distribution systems using metaheuristics - p. 269 21. Chapter 15 Metaheuristic-based automatic generation controller in interconnected power systems with renewable energy sources - p. 293 22. Chapter 16 Route optimization in MANET using swarm intelligence algorithm - p. 313 23. Chapter 17 The promise of metaheuristic algorithms for efficient operation of a highly complex power system - p. 325 24. Chapter 18 Genome sequence assembly using metaheuristics - p. 347 25. Chapter 19 Metaheuristics for optimizing weights in neural networks - p. 359 26. Chapter 20 Metaheuristics for clustering problems - p. 379 27. Chapter 21 Employment of bio-inspired algorithms in the field of antenna array optimization: A review - p. 393 28. Chapter 22 Foundations of combinatorial optimization, heuristics, and metaheuristics - p. 407 29. Index - p. 439
