High-Performance Simulation Based Optimization

Author(s): Thomas Bartz-Beielstein, Bogdan Filipič, Peter Korošec, El-Ghazali Talbi

Series: Studies in Computational Intelligence 833

Publisher: Springer International Publishing, Year: 2020

ISBN: 978-3-030-18763-7;978-3-030-18764-4

 Description:

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. 

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