Into a Deeper Understanding of Evolutionary Computing: Exploration, Exploitation, and Parameter Control : Volume 1

Abdul Hanif Abdul Halim

ISBN 10: 3031740157 / ISBN 13: 9783031740152

Editore: Springer, Springer, 2025

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Druck auf Anfrage Neuware - Printed after ordering - This book delves into fundamental and advanced strategies for enhancing evolutionary and metaheuristic algorithms, focusing on the crucial balance between exploration and exploitation in search mechanisms. As technological advancements increase optimization complexity, effectively managing this balance becomes essential for achieving optimal solutions within reasonable computational resources. The book's distinctive structure organizes content according to optimization stages and processes, offering a comprehensive discussion of various approaches supported by extensive literature.The authors note a scarcity of literature addressing the trade-offs between exploration and exploitation with contemporary references, making this work particularly valuable. It aims to deepen the reader's understanding of evolutionary computing, emphasizing exploration, exploitation, and parameter control. It is relevant not only to algorithm developers and the evolutionary computation community but also to students and researchers across scientific disciplines. The book is designed to be accessible to those without extensive algorithm development backgrounds, providing theoretical and practical insights into optimization methods.

Codice articolo 9783031740152

Dati bibliografici

• Titolo: Into a Deeper Understanding of Evolutionary Computing: Exploration, Exploitation, and Parameter Control : Volume 1
• Editore: Springer, Springer
• Data di pubblicazione: 2025
• Lingua: Inglese
• ISBN 10: 3031740157
• ISBN 13: 9783031740152
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 235 L x 155 A x 17 P (millimetri) 235 millimetri di larghezza per 155 millimetri di altezza per 17 millimetri di profondità
• Peso: 565 grammi

Descrizione articolo

Riassunto

This book delves into fundamental and advanced strategies for enhancing evolutionary and metaheuristic algorithms, focusing on the crucial balance between exploration and exploitation in search mechanisms. As technological advancements increase optimization complexity, effectively managing this balance becomes essential for achieving optimal solutions within reasonable computational resources. The book's distinctive structure organizes content according to optimization stages and processes, offering a comprehensive discussion of various approaches supported by extensive literature.

The authors note a scarcity of literature addressing the trade-offs between exploration and exploitation with contemporary references, making this work particularly valuable. It aims to deepen the reader's understanding of evolutionary computing, emphasizing exploration, exploitation, and parameter control. It is relevant not only to algorithm developers and the evolutionary computation community but also to students and researchers across scientific disciplines. The book is designed to be accessible to those without extensive algorithm development backgrounds, providing theoretical and practical insights into optimization methods.

Dalla quarta di copertina

This book delves into fundamental and advanced strategies for enhancing evolutionary and metaheuristic algorithms, focusing on the vital balance between exploration and exploitation search mechanisms. As technological advancements increase optimization complexity, effectively managing this balance becomes crucial for achieving optimal solutions within reasonable computational resources. The book's distinctive structure organizes content according to optimization stages, offering a comprehensive discussion of various approaches supported by extensive literature.