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Evolutionary Computation for Dynamic Optimization Problems

This book provides a compilation on the state-of-the-art and recent advances of evolutionary computation for dynamic optimization problems. The motivation for this book arises from the fact that many real-world optimization problems and engineering systems are subject to dynamic environments, where changes occur over time. Key issues for addressing dynamic optimization problems in evolutionary computation, including fundamentals, algorithm design, theoretical analysis, and real-world applications, are presented. "Evolutionary Computation for Dynamic Optimization Problems" is a valuable reference to scientists, researchers, professionals and students in the field of engineering and science, particularly in the areas of computational intelligence, nature- and bio-inspired computing, and evolutionary computation.

We would like to thank Dr. Janusz Kacprzyk for inviting us to edit this book in the
Springer book series “Studies in Computational Intelligence”. We acknowledge
the contributors for their fine work and cooperation during the book preparation ...

Evolutionary Computation in Dynamic and Uncertain Environments

This book compiles recent advances of evolutionary algorithms in dynamic and uncertain environments within a unified framework. The book is motivated by the fact that some degree of uncertainty is inevitable in characterizing any realistic engineering systems. Discussion includes representative methods for addressing major sources of uncertainties in evolutionary computation, including handle of noisy fitness functions, use of approximate fitness functions, search for robust solutions, and tracking moving optimums.

1 Explicit Memory Schemes for Evolutionary Algorithms in Dynamic
Environments Shengxiang Yang Department of ... Problem optimization in
dynamic environments has atrracted a growing interest from the evolutionary
computation ...