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

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.

Shows review on state-of-the-art methods of improving the exploration and exploitation of search mechanisms Highlights various concepts of the trade-off improvements Investigates in-depth method of algorithm's parameter improvement

Inhalt

Location size and capacity.- Algorithm Parameters Tuning and Control.- Conclusion and Future Prospects.