THEORY AND PRINCIPLED METHODS FOR THE DESIGN OF METAHEURISTICS by Yossi Borenstein (Editor), Alberto Moraglio (Editor) ( 9783662519554 )

Item Details

Title:

THEORY AND PRINCIPLED METHODS FOR THE DESIGN OF METAHEURISTICS

By:

Yossi Borenstein (Editor), Alberto Moraglio (Editor)

Format:

Paperback

List price:	£76.50
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ISBN 10:

3662519550

ISBN 13:

9783662519554

Publisher:

SPRINGER-VERLAG BERLIN AND HEIDELBERG GMBH & CO. KG

Pub. date:

23 August, 2016

Edition:

Softcover reprint of the original 1st ed. 2014

Series:

Natural Computing Series

Pages:

270

Description:

This book describes methods for incorporating problem knowledge in evolutionary algorithms and other metaheuristics, and shows how statistical methods can use experimental data to enhance the performance of existing metaheuristics in a systematic way.

Synopsis:

Metaheuristics, and evolutionary algorithms in particular, are known to provide efficient, adaptable solutions for many real-world problems, but the often informal way in which they are defined and applied has led to misconceptions, and even successful applications are sometimes the outcome of trial and error. Ideally, theoretical studies should explain when and why metaheuristics work, but the challenge is huge: mathematical analysis requires significant effort even for simple scenarios and real-life problems are usually quite complex. In this book the editors establish a bridge between theory and practice, presenting principled methods that incorporate problem knowledge in evolutionary algorithms and other metaheuristics. The book consists of 11 chapters dealing with the following topics: theoretical results that show what is not possible, an assessment of unsuccessful lines of empirical research; methods for rigorously defining the appropriate scope of problems while acknowledging the compromise between the class of problems to which a search algorithm is applied and its overall expected performance; the top-down principled design of search algorithms, in particular showing that it is possible to design algorithms that are provably good for some rigorously defined classes; and, finally, principled practice, that is reasoned and systematic approaches to setting up experiments, metaheuristic adaptation to specific problems, and setting parameters. With contributions by some of the leading researchers in this domain, this book will be of significant value to scientists, practitioners, and graduate students in the areas of evolutionary computing, metaheuristics, and computational intelligence.

Illustrations:

16 Illustrations, color; 46 Illustrations, black and white; XX, 270 p. 62

Publication:

Germany

Imprint:

Springer-Verlag Berlin and Heidelberg GmbH & Co. K

Returns:

Returnable

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