Overview

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.   


ISBN-13

9783030187637

ISBN-10

3030187632

Weight

1.34 Pounds

Dimensions

6.25 x 1.00 x 9.50 In

List Price

$159.99

Edition

1st Edition

Format

Hardcover

Language

English

Pages

xiii, 291 pages

Publisher

Springer

Published On

2019-06-14



View All Offers

Sort by:

Condition
Seller
Seller Comments
Price
Used, Good
Seller details
Bonita
★★★★☆

Santa Clarita, CA, USA

Access codes and supplements are not guaranteed with used items. May be an ex-library book.
$102.76

 Free delivery by: 30 Mar 2026

Used, Like New
Seller details
GreatBookPrices-
★★★★☆

Columbia, MD, USA

100% Money Back Guarantee. Brand New, Perfect Condition. We offer expedited shipping to all US locat...
$181.14

 Free delivery by: 30 Mar 2026

Brand New
Seller details
GreatBookPrices-
★★★★☆

Columbia, MD, USA

100% Money Back Guarantee. Brand New, Perfect Condition. We offer expedited shipping to all US locat...
$181.14

 Free delivery by: 30 Mar 2026


Bookstores.com relies on cookies to improve your experience.