High-Performance Simulation-Based Optimization

Thomas Bartz-Beielstein (Curatore)

Bogdan Filipic (Curatore)

Springer Nature Switzerland AG, 2020

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.   

• Curatore: Thomas Bartz-Beielstein, Bogdan Filipic
• Editore: Springer Nature Switzerland AG
• Collana: Studies in Computational Intelligence
• Anno: 2020
• Rilegatura: Paperback / softback
• Pagine: 291 p.
• Dimensioni: 235 x 155 mm
• EAN: 9783030187668

Testo in English