Overview
- Provides a complete text to researchers, academicians, graduate students
- Summarizes the evolution of the original SCA in a simplified manner
- Includes numerical examples and MATLAB codes for better understanding of the algorithm
Part of the book series: SpringerBriefs in Applied Sciences and Technology (BRIEFSAPPLSCIENCES)
Part of the book sub series: SpringerBriefs in Computational Intelligence (BRIEFSINTELL)
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Table of contents(6 chapters)
About this book
Authors and Affiliations
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Department of Mathematics, South Asian University, New Delhi, India
Jagdish Chand Bansal, Prathu Bajpai
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Department of Mathematics, National Institute of Technology, Aizawl, India
Anjali Rawat
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School of Mathematics, Computer Science and Engineering, Liverpool Hope University, Liverpool, UK
Atulya K. Nagar
About the authors
Prathu Bajpai is currently pursuing a Ph.D. in Evolutionary and Swarm Algorithms in the faculty of Mathematics and Computer Science at South Asian University. He obtained his master's degree in Mathematics from IIT Gandhinagar India. Nature-inspired algorithms is his major research area.
Anjali Rawat completed her bachelor’s degree from Gargi College, University of Delhi. She obtained her master's degree from South Asian University. Currently, she is pursuing her Ph.D. at the National Institute of Technology, Mizoram. Optimization using meta-heuristics is her majorresearch area.
Atulya K. Nagar holds the Foundation Chair as Professor of Mathematical Sciences and currently he is the Pro-Vice-Chancellor for Research at Liverpool Hope University, United Kingdom. He has been the Founding Dean of the Faculty of Science, and Founding Head of the School of Mathematics, Computer Science and Engineering which he established at the University. He received a prestigious Commonwealth Fellowship for pursuing his doctorate (DPhil) in Applied Nonlinear Mathematics, which he earned from the University of York (UK) in 1996. He holds BSc (Hons), MSc (Mathematics), and MPhil (with distinction) in Mathematics from the MDS University of Ajmer, India. Prior to joining Liverpool Hope, he was with the Department of Mathematical Sciences, and later at the Department of Systems Engineering, at Brunel University, London. He is an internationally respected scholar working at the cutting edge of theoretical computer science, applied mathematical analysis, and systems engineering with his research expertise spanning both applied mathematics and computational methods for nonlinear, complex, and intractable problems arising in science, engineering, and industry. He has edited volumes on Intelligent Systems, and Applied Mathematics. He has been the Editor-in-Chief of the International Journal of Artificial Intelligence and Soft Computing (IJAISC) and serves on editorial boards for a number of prestigious journals; and is one of the co-editors for the Springer Book series on Algorithms for Intelligent Systems (AIS); and for another one on Innovations in Sustainable Technologies and Computing (ISTC). He is well published with over 500 publications in prestigious publishing outlets. Prof Nagar sits on a number of strategic UK wide research bodies such as the JISC Research Strategy group and he is the fellow of the Institute of Mathematics and its Applications (FIMA); and fellow of the Higher Education Academy (FHEA).
Bibliographic Information
Book Title: Sine Cosine Algorithm for Optimization
Authors: Jagdish Chand Bansal, Prathu Bajpai, Anjali Rawat, Atulya K. Nagar
Series Title: SpringerBriefs in Applied Sciences and Technology
DOI: https://doi.org/10.1007/978-981-19-9722-8
Publisher: Springer Singapore
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Author(s) 2023
Softcover ISBN: 978-981-19-9721-1Published: 31 January 2023
eBook ISBN: 978-981-19-9722-8Published: 30 January 2023
Series ISSN: 2191-530X
Series E-ISSN: 2191-5318
Edition Number: 1
Number of Pages: X, 108
Number of Illustrations: 2 b/w illustrations, 19 illustrations in colour
Topics: Computational Intelligence, Optimization, Algorithms