Overview
- Provides a detailed overview of nature inspired optimization techniques from prominent women in the field
- Presents well-defined variables and objective functions and their constraints of various real-life problems in nature inspired optimization
- Includes methodology and criteria for presentation of the solutions obtained
Part of the book series: Women in Engineering and Science (WES)
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About this book
This book gives a detailed information of various real-life applications from various fields using nature inspired optimization techniques. These techniques are proven to be efficient and robust in many difficult problems in literature. The authors provide detailed information about real-life problems and how various nature inspired optimizations are applied to solve these problems. The authors discuss techniques such as Biogeography Based Optimization, Glow Swarm Optimization, Elephant herd Optimization Algorithm, Cuckoo Search Algorithm, Ant Colony Optimization, and Grey Wolf Optimization etc. These algorithms are applied to a wide range of problems from the field of engineering, finance, medicinal etc. As an important part of the Women in Science and Engineering book series, the work highlights the contribution of women leaders in nature inspired optimization, inspiring women and men, girls and boys to enter and apply themselves to the field.
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Keywords
Table of contents (9 chapters)
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Front Matter
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Back Matter
Editors and Affiliations
About the editors
Dr. Dipti Singh, received her PhD from the Indian Institute of Technology, Roorkee studying Optimization Techniques. She currently works at the Department of Applied Mathematics, Gautam Buddha University. She does research in Applied Mathematics. Her area of interest is applications of soft computing techniques in various disciplines of engineering. Her current project is 'forecasting and Analysis of Solid Waste and its Management in India.
Dr. Vanita Garg, received her PhD from the Indian Institute of Technology, Roorkee, studying Applied Mathematics. She teaches at Galgotia University, specializing in Nature Inspired Optimization Techniques. Her research areas include Operational Research, Unconstrained Optimization Problems, Constrained Optimization Problems, and Biogeography Based Optimization Algorithm.
Dr. Kusum Deep, is a full Professor, with the Department of Mathematics, Indian Institute of Technology Roorkee, India and Visiting Professor, Liverpool Hope University, UK and University of Technology Sydney, Australia. With B.Sc Hons & M.Sc Hons. School from Centre for Advanced Studies, Panjab University, Chandigarh, she is an M.Phil Gold Medalist. She earned her PhD from UOR (now IIT Roorkee) in 1988. She has been a national scholarship holder and a Post Doctoral from Loughborough University, UK assisted by International Bursary funded by Commission of European Communities, Brussels. She has won numerous awards like Khosla Research Award, UGC Career Award, Starred Performer of IITR Faculty, best paper awards by Railway Bulletin of Indian Railways, special facilitation in memory of late Prof. M. C. Puri, AIAP Excellence Award. She has authored two books, supervised 20 PhDs, and published 125 research papers. She is a Senior Member of ORSI, CSI, IMS and ISIM. She is the Executive Editor of International Journal of Swarm Intelligence, Inderscience. She is Associate Editor of Swarm and Evolutionary Algorithms, Elsevier and is on the editorial board of many journals. She is the Founder President of Soft Computing Research Society, India. She is the General Chair of series of International Conference on Soft Computing for Problems Solving (SocProS). Her research interests are Evolutionary Algorithms, Swarm Intelligence and nature inspired optimization techniques and their applications.Bibliographic Information
Book Title: Design and Applications of Nature Inspired Optimization
Book Subtitle: Contribution of Women Leaders in the Field
Editors: Dipti Singh, Vanita Garg, Kusum Deep
Series Title: Women in Engineering and Science
DOI: https://doi.org/10.1007/978-3-031-17929-7
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
Hardcover ISBN: 978-3-031-17928-0Published: 03 January 2023
Softcover ISBN: 978-3-031-17931-0Published: 04 January 2024
eBook ISBN: 978-3-031-17929-7Published: 02 January 2023
Series ISSN: 2509-6427
Series E-ISSN: 2509-6435
Edition Number: 1
Number of Pages: X, 204
Number of Illustrations: 7 b/w illustrations, 58 illustrations in colour
Topics: Computational Intelligence, Optimization, Algorithms