Populations can be essential in tracking dynamic optima
Dang, Duc-Cuong and Jansen, Thomas and Lehre, Per Kristian (2016) Populations can be essential in tracking dynamic optima. Algorithmica . ISSN 1432-0541
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 solutions that may be useful in the future. However, rigorous theoretical demonstrations for how populations in dynamic optimisation can be essential are sparse and restricted to special cases.
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