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Advanced Metaheuristics: Novel Approaches for Complex Problem Solving

Advanced Metaheuristics: Novel Approaches for Complex Problem Solving

Inhalt

This book examines a series of strategies designed to enhance metaheuristic algorithms, focusing on critical aspects such as initialization methods, the incorporation of Evolutionary Game Theory to develop novel search mechanisms, and the application of learning concepts to refine evolutionary operators. Furthermore, it emphasizes the significance of diversity and opposition in preventing premature convergence and improving algorithmic efficiency. These strategies collectively contribute to the development of more adaptive and robust optimization techniques. The book was designed from a teaching standpoint, making it suitable for undergraduate and postgraduate students in Science, Electrical Engineering, or Computational Mathematics. Furthermore, engineering practitioners unfamiliar with metaheuristic computations will find value in the application of these techniques to address complex real-world engineering problems, extending beyond theoretical constructs.

Bibliografische Angaben

Mai 2025, 228 Seiten, Studies in Computational Intelligence, Englisch
Springer International Publishing
978-3-031-89283-7

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Weitere Titel der Reihe: Studies in Computational Intelligence

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