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Evolutionary Computation for Dynamic Optimization Problems [electronic resource] / edited by Shengxiang Yang, Xin Yao.

By: Yang, Shengxiang [editor.].
Contributor(s): Yao, Xin [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Studies in Computational Intelligence: 490Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013Description: XXVIII, 470 p. 99 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642384165.Subject(s): Engineering | Artificial intelligence | Engineering | Computational Intelligence | Artificial Intelligence (incl. Robotics)DDC classification: 006.3 Online resources: Click here to access online
Contents:
Part I Fundamentals -- Part II Algorithm Design -- Part III Theoretical Analysis.
In: Springer eBooksSummary: 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.
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Part I Fundamentals -- Part II Algorithm Design -- Part III Theoretical Analysis.

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.

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