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Advanced Techniques for Modifying Metaheuristics
Methods and Applications
- 1st Edition - January 1, 2026
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 3 2 9 7 2 - 2
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 3 2 9 7 3 - 9
Metaheuristics are widely used optimization techniques that have been successfully applied in various real-world problems. However, no single metaheuristic algorithm can solve all… Read more
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Request a sales quoteMetaheuristics are widely used optimization techniques that have been successfully applied in various real-world problems. However, no single metaheuristic algorithm can solve all optimization problems with the same level of efficiency and effectiveness. Advanced Techniques for Modifying Metaheuristics: Methods and Applications covers the latest developments in the field of metaheuristics modification, including theoretical aspects, empirical studies, and practical applications. The book is organized into four main parts, introducing metaheuristics and their basic concepts, the theory and principles of modifying metaheuristics, empirical studies and experimental evaluations of modified metaheuristics, and practical applications of modified metaheuristics in various fields. The modification of metaheuristics has been shown to be a promising approach for improving their performance in solving complex optimization problems. However, there is still a need for more advanced and effective techniques for modifying metaheuristics. This book provides a critical analysis of the strengths and weaknesses of different modification techniques, as well as their suitability for different types of optimization problems. It also covers the latest developments in the field, including the use of machine learning and artificial intelligence techniques for modifying metaheuristics.
• Covers the theoretical aspects of modifying metaheuristics, including the use of machine learning and artificial intelligence techniques.
• Presents empirical studies and experimental evaluations of modified metaheuristics, which is valuable to practitioners who need to know how different modification techniques perform in practice, and to select the most appropriate modification techniques for different types of optimization problems.
• Shows practical applications of modified metaheuristics in various fields, including engineering, finance, and healthcare, enabling both researchers and practitioners to apply modified metaheuristics to real-world problems and understand their impact on different fields.
• Presents empirical studies and experimental evaluations of modified metaheuristics, which is valuable to practitioners who need to know how different modification techniques perform in practice, and to select the most appropriate modification techniques for different types of optimization problems.
• Shows practical applications of modified metaheuristics in various fields, including engineering, finance, and healthcare, enabling both researchers and practitioners to apply modified metaheuristics to real-world problems and understand their impact on different fields.
Computer Science researchers, artificial intelligence researchers, and researchers and practitioners working in the field of optimization, metaheuristics, and computational intelligence. The primary audience also includes data analysts, software engineers, as well as researchers and professionals across the fields of science and engineering.
CHAPTER 1: Introduction
CHAPTER 2: Overview of metaheuristics and their applications
CHAPTER 3: Motivation for modifying metaheuristics
CHAPTER 4: Aims and objectives of the book
CHAPTER 5: Metaheuristic Algorithms and Their Limitations
CHAPTER 6: Brief overview of classical metaheuristic algorithms
CHAPTER 7: Limitations of classical metaheuristic algorithms
CHAPTER 8: Need for modifying metaheuristics
CHAPTER 9: Review of Advanced Techniques for Modifying Metaheuristics
CHAPTER 10: Review of literature on advanced techniques for modifying metaheuristics
CHAPTER 11: Taxonomy of advanced techniques for modifying metaheuristics
CHAPTER 12: Comparative analysis of advanced techniques for modifying metaheuristics
CHAPTER 13: Evolutionary Algorithm-Based Modifications
CHAPTER 14: Overview of evolutionary algorithms
CHAPTER 15: Modifications based on population diversity
CHAPTER 16: Modifications based on parent selection
CHAPTER 17: Modifications based on mutation and crossover operators
CHAPTER 18: Experimental evaluation of evolutionary algorithm-based modifications
CHAPTER 19: Swarm Intelligence-Based Modifications
CHAPTER 20: Overview of swarm intelligence algorithms
CHAPTER 21: Modifications based on communication strategies
CHAPTER 22: Modifications based on individual behavior
CHAPTER 23: Modifications based on collective behavior
CHAPTER 24: Experimental evaluation of swarm intelligence-based modifications
CHAPTER 25: Hybrid Approaches for Modifying Metaheuristics
CHAPTER 26: Overview of hybrid metaheuristics
CHAPTER 27: Integration of advanced techniques into hybrid metaheuristics
CHAPTER 28: Case studies on hybrid approaches for modifying metaheuristics
CHAPTER 29: Applications of Modified Metaheuristics
CHAPTER 30: Applications of modified metaheuristics in engineering and design optimization
CHAPTER 31: Applications of modified metaheuristics in finance and economics
CHAPTER 32: Applications of modified metaheuristics in healthcare and medical diagnosis
CHAPTER 33: Applications of modified metaheuristics in social sciences and humanities
CHAPTER 34: Empirical Evaluation of Modified Metaheuristics
CHAPTER 35: Experimental evaluation frameworks for modified metaheuristics
CHAPTER 36: Performance evaluation measures for modified metaheuristics
CHAPTER 37: Case studies on empirical evaluation of modified metaheuristics
CHAPTER 38: Future Directions and Emerging Trends
CHAPTER 39: Emerging trends in modifying metaheuristics
CHAPTER 40: Future directions and challenges in modifying metaheuristics
CHAPTER 41: Potential applications and impact of modified metaheuristics
CHAPTER 2: Overview of metaheuristics and their applications
CHAPTER 3: Motivation for modifying metaheuristics
CHAPTER 4: Aims and objectives of the book
CHAPTER 5: Metaheuristic Algorithms and Their Limitations
CHAPTER 6: Brief overview of classical metaheuristic algorithms
CHAPTER 7: Limitations of classical metaheuristic algorithms
CHAPTER 8: Need for modifying metaheuristics
CHAPTER 9: Review of Advanced Techniques for Modifying Metaheuristics
CHAPTER 10: Review of literature on advanced techniques for modifying metaheuristics
CHAPTER 11: Taxonomy of advanced techniques for modifying metaheuristics
CHAPTER 12: Comparative analysis of advanced techniques for modifying metaheuristics
CHAPTER 13: Evolutionary Algorithm-Based Modifications
CHAPTER 14: Overview of evolutionary algorithms
CHAPTER 15: Modifications based on population diversity
CHAPTER 16: Modifications based on parent selection
CHAPTER 17: Modifications based on mutation and crossover operators
CHAPTER 18: Experimental evaluation of evolutionary algorithm-based modifications
CHAPTER 19: Swarm Intelligence-Based Modifications
CHAPTER 20: Overview of swarm intelligence algorithms
CHAPTER 21: Modifications based on communication strategies
CHAPTER 22: Modifications based on individual behavior
CHAPTER 23: Modifications based on collective behavior
CHAPTER 24: Experimental evaluation of swarm intelligence-based modifications
CHAPTER 25: Hybrid Approaches for Modifying Metaheuristics
CHAPTER 26: Overview of hybrid metaheuristics
CHAPTER 27: Integration of advanced techniques into hybrid metaheuristics
CHAPTER 28: Case studies on hybrid approaches for modifying metaheuristics
CHAPTER 29: Applications of Modified Metaheuristics
CHAPTER 30: Applications of modified metaheuristics in engineering and design optimization
CHAPTER 31: Applications of modified metaheuristics in finance and economics
CHAPTER 32: Applications of modified metaheuristics in healthcare and medical diagnosis
CHAPTER 33: Applications of modified metaheuristics in social sciences and humanities
CHAPTER 34: Empirical Evaluation of Modified Metaheuristics
CHAPTER 35: Experimental evaluation frameworks for modified metaheuristics
CHAPTER 36: Performance evaluation measures for modified metaheuristics
CHAPTER 37: Case studies on empirical evaluation of modified metaheuristics
CHAPTER 38: Future Directions and Emerging Trends
CHAPTER 39: Emerging trends in modifying metaheuristics
CHAPTER 40: Future directions and challenges in modifying metaheuristics
CHAPTER 41: Potential applications and impact of modified metaheuristics
- No. of pages: 350
- Language: English
- Edition: 1
- Published: January 1, 2026
- Imprint: Morgan Kaufmann
- Paperback ISBN: 9780443329722
- eBook ISBN: 9780443329739