Memetic algorithms are evolutionary algorithms that apply a local search process to refine solutions to hard problems. This monograph presents a gallery of works on memetic algorithms. It focuses on this technology as the central topical matter. It gives an integrated view on both good practice examples and trends. Editor(s): Hart, William E; Krasnogor, Natalio; Smith, James E. Series: Studies in Fuzziness and Soft Computing. Num Pages: 410 pages, biography. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 23. Weight in Grams: 769. . 2004. Hardback. . . . .

N� de ref. del art�culo V9783540229049

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Detalles bibliogr�ficos

T�tulo: Recent Advances in Memetic Algorithms
Editor: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Fecha de publicaci�n: 2004
Idioma: Ingl�s
ISBN 10: 3540229043
ISBN 13: 9783540229049
Encuadernaci�n: Encuadernaci�n de tapa dura
Estado: New

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Sinopsis

Memetic algorithms are evolutionary algorithms that apply a local search process to refine solutions to hard problems. Memetic algorithms are the subject of intense scientific research and have been successfully applied to a multitude of real-world problems ranging from the construction of optimal university exam timetables, to the prediction of protein structures and the optimal design of space-craft trajectories. This monograph presents a rich state-of-the-art gallery of works on memetic algorithms. Recent Advances in Memetic Algorithms is the first book that focuses on this technology as the central topical matter. This book gives a coherent, integrated view on both good practice examples and new trends including a concise and self-contained introduction to memetic algorithms. It is a necessary read for postgraduate students and researchers interested in recent advances in search and optimization technologies based on memetic algorithms, but can also be used as complement to undergraduate textbooks on artificial intelligence.

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Memetic algorithms are evolutionary algorithms that apply a local search process to refine solutions to hard problems. Memetic algorithms are the subject of intense scientific research and have been successfully applied to a multitude of real-world problems ranging from the construction of optimal university exam timetables, to the prediction of protein structures and the optimal design of space-craft trajectories. "Recent Advances in Memetic Algorithms" presents a rich state-of-the-art gallery of works on Memetic algorithms. Recent Advances in Memetic Algorithms is the first book that focuses on this technology as the central topical matter. This monograph gives a coherent, integrated view on both good practice examples and new trends including a concise and self-contained introduction to Memetic Algorithms. It is a necessary read for postgraduate students and researchers interested in recent advances in search and optimization technologies based on Memetic algorithms, but can also be used as complement to undergraduate textbooks on artificial intelligence.

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