Mirjalili / Gandomi | Comprehensive Metaheuristics | Buch | 978-0-323-91781-0 | sack.de

Buch, Englisch, 500 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 930 g

Mirjalili / Gandomi

Comprehensive Metaheuristics

Algorithms and Applications
Erscheinungsjahr 2023
ISBN: 978-0-323-91781-0
Verlag: William Andrew Publishing

Algorithms and Applications

Buch, Englisch, 500 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 930 g

ISBN: 978-0-323-91781-0
Verlag: William Andrew Publishing


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.
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Zielgruppe


<p>Researchers, developers, and industry professionals in Information Technology and Computer Science, such as developers of AI, Machine Learning, and Deep Learning, as well as other research fields, including Biomedical. </p>

Weitere Infos & Material


1. Chaos theory in metaheuristcs

2. A New Metaheuristic Approach for Solving Multi-Objective Optimization Problems

3. A Brief Overview of Physics-inspired Metaheuristic Optimization Techniques

4. Application of evolutionary computation techniques for developing optimal response actions against water distribution networks contamination

5. Metaheuristic Technique for Solving Fuzzy Nonlinear Equations

6. Meta-heuristics in Network Intrusion Detection

7. Meta-heuristics in text clustring

8. Application of Metaheuristic Algorithms for Optimal Design of Sewer Collection Systems

9. Meta-heuristics for optimization of structures

10. Meta-heuristics for solving wind turbine placement problem

11. Meta-heuristics in industrial development and its future perspective

12. Levy Flight and Chaos Theory Based Gravitational Search Algorithm for Greyscale Image Thresholding

13. Meta-heuristics for Optimal Feature Selection in High-Dimensional Datasets

14. The Optimal Deployment of Sensors for Leakage Detection in Water Distribution Systems using meta-heuristics

15. Meta-Heuristics Based Automatic Generation Controller In Interconnected Power Systems With Renewable Energy Sources

16. Swarm Intelligence based Route optimization in Mobile Ad-hoc Network

17. The promise of metaheuristic algorithms for efficient operation of a highly complex power system: a comparative assessment

18. Genome Sequencing: Applications of Meta-Heuristics in Bioinformatics

19. Meta-heuristics for training Neural Networks

20. Meta-heuristics for clustring problems

21. Bio Inspired Algorithms in the field of Antenna Array Optimization: Review

22. Foundations of Combinatorial Optimization, Heuristics, and Meta-heuristics


Mirjalili, Ali
Senior lecturer S. Ali Mirjalili MD, PhD, PGDipSurgAnat, PGCertCPU works in the Anatomy and Medical Imaging Department and Convenor of Science for Surgens Course, Department of Surgery at University of Auckland, Malaysia.

Gandomi, Amir Hossein
Dr. Amir H. Gandomi is anARC DECRA Fellow at the Faculty of Engineering andInformation Technology, University of Technology Sydney, Australia. Prior to joining UTS, Dr. Gandomi was an Assistant Professor at Stevens Institute of Technology, USA and a Distinguished Research Fellow in BEACON center, Michigan State University, USA. Dr. Gandomi has published over two hundred journal papers and seven books which collectively have been cited 19,000+ times. He has been named as one of the most influential scientific mindsand Highly Cited Researcher (top 1% publications and 0.1% researchers) for four consecutive years, 2017 to 2020. He also ranked 18th in GP bibliography among more than 12,000 researchers. He has served as associate editor, editor and guest editor in several prestigious journals such as AE of SWEVO, IEEE TBD, and IEEE IoTJ. Dr. Gandomi is active in delivering keynotes and invited talks. His research interests are global optimization andbigdata analytics using Machine Learning and evolutionary computations in particular.


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