Genetic algorithm essentials / Oliver Kramer.

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Genetic algorithm essentials / Oliver Kramer.

9783319521565 (electronic book)
331952156X (electronic book)
9783319521558

Cham, Switzerland : Springer, 2017.

English

1 online resource (ix, 92 pages) : color illustrations.

10.1007/978-3-319-52156-5 doi

QA402.5

519.6/25

This book introduces readers to genetic algorithms (GAs) with an emphasis on making the concepts, algorithms, and applications discussed as easy to understand as possible. Further, it avoids a great deal of formalisms and thus opens the subject to a broader audience in comparison to manuscripts overloaded by notations and equations. The book is divided into three parts, the first of which provides an introduction to GAs, starting with basic concepts like evolutionary operators and continuing with an overview of strategies for tuning and controlling parameters. In turn, the second part focuses on solution space variants like multimodal, constrained, and multi-objective solution spaces. Lastly, the third part briefly introduces theoretical tools for GAs, the intersections and hybridizations with machine learning, and highlights selected promising applications.

Includes bibliographical references and index.

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text file PDF

Online resource; title from PDF title page (SpringerLink, viewed January 19, 2017).

Studies in computational intelligence ; v. 679.

Print version: 9783319521558

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