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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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| Pubblicato in: | Algorithmica |
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| Autori principali: | , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Springer US
2016
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5479466/ https://ncbi.nlm.nih.gov/pubmed/28690348 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s00453-016-0187-y |
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