High-Performance Simulation-Based Optimization (1st ed. 2020) (Studies in Computational Intelligence #833)

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Synopsis
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.
Copyright:
2020

Book Details

Book Quality:
Publisher Quality
ISBN-13:
9783030187644
Related ISBNs:
9783030187637
Publisher:
Springer International Publishing
Date of Addition:
Copyrighted By:
Springer Nature Switzerland AG
Adult content:
No
Language:
English
Has Image Descriptions:
No
Categories:
Nonfiction, Computers and Internet, Technology
Submitted By:
Bookshare Staff
Usage Restrictions:
This is a copyrighted book.
Edited by:
Thomas Bartz-Beielstein
Edited by:
Bogdan Filipič
Edited by:
Peter Korošec
Edited by:
El-Ghazali Talbi

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