Performance Prediction and Analytics of Fuzzy, Reliability and Queuing Models. Theory and Applications.

Deep, K. et al (Eds.)

ISBN 10: 981130856X / ISBN 13: 9789811308567

Published by Singapore, Springer., 2019

About this Item

vii, 282 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch.

Seller Inventory # 12040DB

Bibliographic Details

• Title: Performance Prediction and Analytics of Fuzzy, Reliability and Queuing Models. Theory and Applications.
• Publisher: Singapore, Springer.
• Publication Date: 2019
• Language: English
• ISBN 10: 981130856X
• ISBN 13: 9789811308567
• Binding: Hardcover
• Seller catalogs:
  • Wirtschaftswissenschaften

About this title

Synopsis

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. 

About the Author

Dr. 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. Madhu Jain is an Associate Professor at the Department of Mathematics, Indian Institute of Technology Roorkee. Her research interests include computer communications networks, performance prediction of wireless systems, mathematical modeling, and biomathematics.  

Dr. Said Salhi is Director of the Centre for Logistics & Heuristic Optimization (CLHO) at Kent Business School, University of Kent, UK. Prior to his appointment at Kent in 2005, Said served at the University of Birmingham’s School of Mathematics for 15 years, where in the latter years he acted as Head of the Management Mathematics Group. He obtained his BSc in Mathematics at Algiers’s University, and his MSc and PhD in OR at Southampton (Institute of Mathematics) and Lancaster (School of Management), respectively. Dr. Said has edited 6 special journal issues, chaired the European Working Group in Location Analysis in 1996 and recently the International Symposium on Combinatorial Optimisation (CO2016) in Kent, 1–3 September 2016. He has published over 100 papers in academic journals.