Performance Prediction and Analytics of Fuzzy, Reliability and Queuing Models by Kusum Deep

Performance Prediction and Analytics of Fuzzy, Reliability and Queuing Models by Kusum Deep

This book presents the latest developments and breakthroughs in fuzzy theory and performance prediction of queuing and reliability models by using the stochastic modeling and optimization theory. The main focus is on analytics that use fuzzy logic, queuing and reliability theory for the performance prediction and optimal design of real-time engineering systems including call centers, telecommunication, manufacturing, service organizations, etc. For the day-to-day as well as industrial queuing situations and reliability prediction of machining parts embedded in computer, communication and manufacturing systems, the book assesses various measures of performance and effectiveness that can provide valuable insights and help arrive at the best decisions with regard to service and engineering systems. 

In twenty chapters, the book presents both theoretical developments and applications of the fuzzy logic, reliability and queuing models in a diverse range of scenarios. The topics discussed will be of interest to researchers, educators and undergraduate students in the fields of Engineering, Business Management, and the Mathematical Sciences. 

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	9789811345197
ISBN 10	9811345198
Title	Performance Prediction and Analytics of Fuzzy, Reliability and Queuing Models
Author	Kusum Deep
Series	Asset Analytics
Condition	Unavailable
Binding Type	Paperback
Publisher	Springer Verlag, Singapore
Year published	2019-02-02
Number of pages	282
Cover note	Book picture is for illustrative purposes only, actual binding, cover or edition may vary.