Decision Science in Action by Kusum Deep

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Summary

This book provides essential insights into a range of newly developed numerical optimization techniques with a view to solving real-world problems.

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Decision Science in Action by Kusum Deep

This book provides essential insights into a range of newly developed numerical optimization techniques with a view to solving real-world problems. Many of these problems can be modeled as nonlinear optimization problems, but due to their complex nature, it is not always possible to solve them using conventional optimization theory. Accordingly, the book discusses the design and applications of non-conventional numerical optimization techniques, including the design of benchmark functions and the implementation of these techniques to solve real-world optimization problems. 

The book’s twenty chapters examine various interesting research topics in this area, including: Pi fraction-based optimization of the Pantoja–Bretones–Martin (PBM) antenna benchmarks; benchmark function generators for single-objective robust optimization algorithms; convergence of gravitational search algorithms on linear and quadratic functions; and an algorithm for the multi-variant evolutionary synthesis of nonlinear models with real-valued chromosomes.

Delivering on its promise to explore real-world scenarios, the book also addresses the seismic analysis of a multi-story building with optimized damper properties; the application of constrained spider monkey optimization to solve portfolio optimization problems; the effect of upper body motion on a bipedal robot’s stability; an ant colony algorithm for routing alternate-fuel vehicles in multi-depot vehicle routing problems; enhanced fractal dimension-based feature extraction for thermal face recognition; and an artificial bee colony-based hyper-heuristic for the single machine order acceptance and scheduling problem.

The book will benefit not only researchers, but also organizations active in such varied fields as Aerospace, Automotive, Biotechnology, Consumer Packaged Goods, Electronics, Finance, Business & Banking, Oil, Gas & Geosciences, and Pharma, to name a few. 

Atulya K. Nagar holds the Foundation Chair as Professor of Mathematical Sciences, and is the Pro-Vice-Chancellor for Research and Dean of the Faculty of Science at Liverpool Hope University, United Kingdom. He is also the Head of the School of Mathematics, Computer Science and Engineering, which he established at the University. He is an internationally respected scholar working at the cutting edge of theoretical computer science, applied mathematical analysis, operations research, and systems engineering. He received a prestigious Commonwealth Fellowship to pursue his doctorate (DPhil) in Applied Nonlinear Mathematics, which he earned from the University of York (UK) in 1996. He holds a BSc (Hons), an MSc and MPhil (with distinction) in Mathematical Physics from the MDS University of Ajmer, India. His research expertise spans both applied mathematics and computational methods for nonlinear, complex, and intractable problems arising in science, engineering and industry. Prof. Kusum Deep is a Professor at the Department of Mathematics, Indian Institute of Technology Roorkee. Her research interests include numerical optimization, nature inspired optimization, computational intelligence, genetic algorithms, parallel genetic algorithms, and parallel particle swarm optimization. Dr. Jagdish Chand Bansal is an Assistant Professor at the South Asian University, New Delhi, India and visiting research fellow at Liverpool Hope University, UK. He has an excellent academic record and is a leading researcher in the field of swarm intelligence. He has published numerous research papers in respected international and national journals. Dr. Kedar Nath Das is an Assistant Professor at the Department of Mathematics, National Institute of Technology, Silchar, Assam, India. Over the past 10 years, he has made substantial contributions to research on soft computing, and has published several papers in prominent national and international journals. His chief area of interest is evolutionary and bio-inspired algorithms for optimization.
SKU Unavailable
ISBN 13 9789811345203
ISBN 10 9811345201
Title Decision Science in Action
Author Kusum Deep
Series Asset Analytics
Condition Unavailable
Binding Type Paperback
Publisher Springer Verlag, Singapore
Year published 2019-01-11
Number of pages 276
Cover note Book picture is for illustrative purposes only, actual binding, cover or edition may vary.