Achieving a better solution or improving the performance of existing system design is an ongoing process for which scientists, engineers, mathematicians and researchers have been striving for many years. The purpose of this book is to describe the fundamentals, background and theoretical concepts of optimization principles in a comprehensive manner, along with their potential applications and implementation strategies. Focus is on case studies and real time applications as well as current research directions. Useful for a wide spectrum of target readers including students and researchers in academia and industry, discussion on linear programming is included, along with multi-variable methods for risk assessment, nonlinear methods, ant colony optimization, particle swarm optimization, multi-criterion and topology optimization, learning classifier, case studies on six sigma, performance measures and evaluation, multi-objective optimization problems, machine learning approaches, genetic algorithms and quality of service optimizations.
| ISBN: | 9780750324021 |
| Publication date: | 20th November 2019 |
| Author: | G R Sinha |
| Publisher: | IOP Publishing an imprint of Institute of Physics Publishing |
| Format: | Hardback |
| Pagination: | 433 pages |
| Series: | IOP Ebooks |
| Genres: |
Optimization |
Achieving a better solution or improving the performance of existing system design is an ongoing process for which scientists, engineers, mathematicians and researchers have been striving for many years. The purpose of this book is to describe the fundamentals, background and theoretical concepts of optimization principles in a comprehensive manner, along with their potential applications and implementation strategies. Focus is on case studies and real time applications as well as current research directions. Useful for a wide spectrum of target readers including students and researchers in academia and industry, discussion on linear programming is included, along with multi-variable methods for risk assessment, nonlinear methods, ant colony optimization, particle swarm optimization, multi-criterion and topology optimization, learning classifier, case studies on six sigma, performance measures and evaluation, multi-objective optimization problems, machine learning approaches, genetic algorithms and quality of service optimizations.
Modern Optimization Methods for Science, Engineering and Technology features in the following genres: Optimization
Modern Optimization Methods for Science, Engineering and Technology is available in Hardback
Modern Optimization Methods for Science, Engineering and Technology was written by G R Sinha and published by IOP Publishing an imprint of Institute of Physics Publishing
Modern Optimization Methods for Science, Engineering and Technology has 433 pages
Yes it is part of IOP Ebooks series
£108.00