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[Studies in Computational Intelligence] Evolutionary Computation in Dynamic and Uncertain Environments Volume 51 || Learning and Anticipation in Online Dynamic Optimization

✍ Scribed by Yang, Shengxiang; Ong, Yew-Soon; Jin, Yaochu

Book ID
120787986
Publisher
Springer Berlin Heidelberg
Year
2007
Tongue
German
Weight
980 KB
Category
Article
ISBN
3540497749

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✦ Synopsis

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.

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[Studies in Computational Intelligence]
[Studies in Computational Intelligence] Evolutionary Computation for Dynamic Optimization Problems Volume 490 || A Comparative Study on Particle Swarm Optimization in Dynamic Environments
✍ Yang, Shengxiang; Yao, Xin πŸ“‚ Article πŸ“… 2013 πŸ› Springer Berlin Heidelberg 🌐 English βš– 506 KB

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