Populations can be essential in tracking dynamic optima

Real-world optimisation problems are often dynamic. Previously good solutions must be updated or replaced due to changes in objectives and constraints. It is often claimed that evolutionary algorithms are particularly suitable for dynamic optimisation because a large population can contain different...

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Bibliographic Details
Main Authors: Dang, Duc-Cuong, Jansen, Thomas, Lehre, Per Kristian
Format: Article
Published: Springer 2016
Subjects:
Online Access:https://eprints.nottingham.ac.uk/34913/

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