The field of metaheuristic optimization has experienced a surge in novel algorithmic developments in recent years, yet there is a lack of consolidated resources focusing on these innovations, especially their categorization and applications in solving real-world problems. This work fills the gap by categorizing and detailing the most recently developed metaheuristic optimization algorithms into local, global, and hybrid methods. The authors explore various optimization algorithms like Runge Kutta Optimization, Manta Ray Foraging Optimization, and Hybrid Marine Predators Algorithm, explaining their mechanisms, pseudocode, and advantages. It also provides case studies to demonstrate their practical applications in fields like supply chain management, robotics, energy optimization, and so on. Thus, the work bridges the gap between theory and application, offering insights that will inspire further innovation and practical implementation of modern optimization techniques.
eBook - ePub
Metaheuristic Optimization Algorithms
For Local Techniques, Global Techniques, and Hybrid Techniques
- 283 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
eBook - ePub
Metaheuristic Optimization Algorithms
For Local Techniques, Global Techniques, and Hybrid Techniques
About this book
Information
Table of contents
- Title Page
- Copyright
- Contents
- Frontmatter
- Contents
- About Authors
- Part 1: Foundations of metaheuristic optimization
- Part 2: Recent local optimization algorithms
- Part 3: Recent global optimization algorithms
- Part 4: Hybrid metaheuristic algorithms
- Part 5: Applications and future directions
- Index
- Index
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Yes, you can access Metaheuristic Optimization Algorithms by Kaushik Kumar,Ritesh Kumar Singh,Sanjiv Kumar Tiwari,Chikesh Ranjan in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over 1.5 million books available in our catalogue for you to explore.