Advances in Evolutionary Algorithms : Theory, Design and Practice

Chang Wook Ahn

ISBN 10: 3540317589 / ISBN 13: 9783540317586

Editore: Springer Berlin Heidelberg, 2006

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Druck auf Anfrage Neuware - Printed after ordering - Every real-world problem from economic to scientific and engineering fields is ultimately confronted with a common task, viz., optimization. Genetic and evolutionary algorithms (GEAs) have often achieved an enviable success in solving optimization problems in a wide range of disciplines. The goal of this book is to provide effective optimization algorithms for solving a broad class of problems quickly, accurately, and reliably by employing evolutionary mechanisms. In this regard, five significant issues have been investigated: Bridging the gap between theory and practice of GEAs, thereby providing practical design guidelines. Demonstrating the practical use of the suggested road map. Offering a useful tool to significantly enhance the exploratory power in time-constrained and memory-limited applications. Providing a class of promising procedures that are capable of scalably solving hard problems in the continuous domain. Opening an important track for multiobjective GEA research that relies on decomposition principle. This book serves to play a decisive role in bringing forth a paradigm shift in future evolutionary computation.

Codice articolo 9783540317586

Dati bibliografici

• Titolo: Advances in Evolutionary Algorithms : Theory, Design and Practice
• Editore: Springer Berlin Heidelberg
• Data di pubblicazione: 2006
• Lingua: Inglese
• ISBN 10: 3540317589
• ISBN 13: 9783540317586
• Rilegatura: Buch
• Condizione: Neu
• Dimensioni: 241 L x 160 A x 15 P (millimetri) 241 millimetri di larghezza per 160 millimetri di altezza per 15 millimetri di profondità
• Peso: 453 grammi

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Riassunto

Genetic and evolutionary algorithms (GEAs) have often achieved an enviable success in solving optimization problems in a wide range of disciplines. This book provides effective optimization algorithms for solving a broad class of problems quickly, accurately, and reliably by employing evolutionary mechanisms.

Dalla quarta di copertina

Genetic and evolutionary algorithms (GEAs) have often achieved an enviable success in solving optimization problems in a wide range of disciplines. The goal of this book is to provide effective optimization algorithms for solving a broad class of problems quickly, accurately, and reliably by employing evolutionary mechanisms. In this regard, five significant issues have been investigated:

• Bridging the gap between theory and practice of GEAs, thereby providing practical design guidelines.
• Demonstrating the practical use of the suggested road map.
• Offering a useful tool to significantly enhance the exploratory power in time-constrained and memory-limited applications.
• Providing a class of promising procedures that are capable of scalably solving hard problems in the continuous domain.
• Opening an important track for multiobjective GEA research that relies on decomposition principle.

This book serves to play a decisive role in bringing forth a paradigm shift in future evolutionary computation.