Comprehensive Metaheuristics

Algorithms and Applications

1st Edition - January 31, 2023
Editors: Ali Mirjalili, Amir Hossein Gandomi
Language: English
Paperback ISBN:
9 7 8 - 0 - 3 2 3 - 9 1 7 8 1 - 0
eBook ISBN:
9 7 8 - 0 - 3 2 3 - 9 7 2 6 7 - 3

Comprehensive Metaheuristics: Algorithms and Applications presents the foundational underpinnings of metaheuristics and a broad scope of algorithms and real-world applicati… Read more

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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.

Cover image
Title page
Table of Contents
Copyright
Contributors
Chapter 1: Chaos theory in metaheuristics
Abstract
1: Introduction
2: Chaos system and chaotic maps
3: Chaotic strategies in metaheuristic optimization
4: An application with chaotic system
References
Chapter 2: Metaheuristic approaches for solving multiobjective optimization problems
Abstract
1: Introduction
2: Related works
3: An overview of electric fish optimization
4: Multiobjective electric fish optimization algorithm
5: Experiments
6: Conclusion
References
Chapter 3: A brief overview of physics-inspired metaheuristics
Abstract
1: Introduction
2: Classical mechanics-based metaheuristics
3: Fluid mechanics-based metaheuristics
4: Thermodynamics-based metaheuristics
5: Electromagnetism-based metaheuristics
6: Optics-based metaheuristics
7: Other physics-based metaheuristic algorithms
8: Conclusion
References
Chapter 4: Evolutionary computation techniques for optimal response actions against water distribution networks contamination
Abstract
1: Introduction
2: Evolutionary computation
3: Methodology development and applications
4: Conclusion
References
Chapter 5: Metaheuristic technique for solving fuzzy nonlinear equations
Abstract
Acknowledgments
1: Introduction
2: Preliminaries
3: A brief description of the GBO algorithm
4: Numerical examples
5: Conclusion
References
Chapter 6: Metaheuristic algorithms in network intrusion detection
Abstract
1: Introduction
2: Metaheuristic algorithms
3: Methodology
4: Metaheuristic algorithms in IDS
5: Challenges and future direction
6: Conclusion
References
Chapter 7: Metaheuristic algorithms in text clustering
Abstract
1: Introduction
2: Text clustering formulation procedure
3: Metaheuristic algorithms application in text clustering
4: Conclusion and possible future research focus
References
Chapter 8: Application of metaheuristic algorithms in optimal design of sewer collection systems
Abstract
1: Introduction
2: Sewer collection systems
3: Metaheuristic algorithms
4: Applications
5: Summary and conclusion
References
Chapter 9: Space truss structures’ optimization using metaheuristic optimization algorithms
Abstract
1: Introduction
2: African vulture optimization algorithm, artificial gorilla troops optimizer, and artificial hummingbird algorithms
3: Structural design optimization
4: Conclusion
References
Chapter 10: Metaheuristics for solving the wind turbine placement problem
Abstract
1: Introduction
2: Artificial gorilla troops optimizers
3: Binary variants of artificial gorilla troops optimizers
4: Experimental setup
5: Results and discussion
6: Conclusion
References
Chapter 11: Use of metaheuristics in industrial development and their future perspectives
Abstract
1: Introduction
2: Classification of metaheuristics
3: Optimization in industry
4: Future perspective of metaheuristics in industrial development
5: Conclusion
References
Chapter 12: Lévy flight and Chaos theory based metaheuristics for grayscale image thresholding
Abstract
Conflict of interest
1: Introduction
2: Literature survey
3: Gravitational search algorithm
4: Lévy flight and chaos theory-based gravitational search algorithm
5: Image segmentation using LCGSA technique
6: Experimental results and discussion
7: Conclusion and future scope
References
Chapter 13: Metaheuristics for optimal feature selection in high-dimensional datasets
Abstract
1: Introduction
2: Characteristics of high-dimensional data
3: Feature selection in high-dimensional datasets
4: Metaheuristic approaches
5: Practical evaluation
6: Conclusion
References
Chapter 14: Optimal deployment of sensors for leakage detection in water distribution systems using metaheuristics
Abstract
1: Introduction
2: Background
3: Related works
4: Methods
5: Objective functions
6: Computational experiments
7: Conclusions
References
Chapter 15: Metaheuristic-based automatic generation controller in interconnected power systems with renewable energy sources
Abstract
1: Introduction
2: Renewable energy sources integrated power systems
3: The proposed PID-(1 + I) controller
4: Metaheuristic optimization techniques
5: Simulation results and discussions
6: Conclusion
References
Chapter 16: Route optimization in MANET using swarm intelligence algorithm
Abstract
1: Introduction
2: Related work
3: Workflow of MANETs
4: Routing challenges in MANETs
5: Routing issues resolved by optimization
6: Comparative analysis
7: Conclusion
References
Chapter 17: The promise of metaheuristic algorithms for efficient operation of a highly complex power system
Abstract
1: Introduction
2: Reptile search algorithm
3: Problem statement
4: Case study
5: Conclusions
References
Chapter 18: Genome sequence assembly using metaheuristics
Abstract
1: Introduction
2: Past works
3: Genome sequencing
4: Combinatorial optimization
5: Experiments
6: Conclusions
References
Chapter 19: Metaheuristics for optimizing weights in neural networks
Abstract
1: Introduction
2: Feedforward neural networks
3: Proposed algorithm
4: Experiments and results
5: Conclusion and future work
References
Chapter 20: Metaheuristics for clustering problems
Abstract
1: Introduction
2: Data clustering problem
3: Data clustering using metaheuristic algorithms
4: Results and discussion
5: Conclusion and future works
References
Chapter 21: Employment of bio-inspired algorithms in the field of antenna array optimization: A review
Abstract
1: Introduction
2: Flower pollination algorithm
3: Cat Swarm Optimization
4: Gravitational Search Algorithm
5: Case study
6: Conclusion
References
Chapter 22: Foundations of combinatorial optimization, heuristics, and metaheuristics
Abstract
1: Introduction
2: Combinatorial optimization problems
3: Analysis of algorithms
4: Complexity of algorithms
5: Modeling a CO problem
6: Solution methods
7: Conclusion
References
Index

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