| Title | : | High-Performance Simulation-Based Optimization |
|---|---|---|
| Author | : | Thomas Bartz-Beielstein, Bogdan Filipič, Peter Korošec & El-Ghazali Talbi |
| Release | : | 2019-06-01 |
| Kind | : | ebook |
| Genre | : | Computers & Internet, Books, Professional & Technical, Engineering, Electrical Engineering |
| Size | : | 23490907 |
| This book presents the state of the art in designing high-performance algorithms that combine simulation and optimization in order to solve complex optimization problems in science and industry, problems that involve time-consuming simulations and expensive multi-objective function evaluations. As traditional optimization approaches are not applicable per se, combinations of computational intelligence, machine learning, and high-performance computing methods are popular solutions. But finding a suitable method is a challenging task, because numerous approaches have been proposed in this highly dynamic field of research. That’s where this book comes in: It covers both theory and practice, drawing on the real-world insights gained by the contributing authors, all of whom are leading researchers. Given its scope, if offers a comprehensive reference guide for researchers, practitioners, and advanced-level students interested in using computational intelligence and machine learning to solve expensive optimization problems. |
