Du Plessis, M.C. (Mathys Cornelius)Engelbrecht, Andries P.2014-11-032014-11-032013-01Du Plessis, MC & Engelbrecht, AP 2013, 'Differential evolution for dynamic environments with unknown numbers of optima', Journal of Global Optimization, vol.55, no. 1, pp. 73-99.0925-5001 (print)1573-2916 (online)10.1007/s10898-012-9864-9http://hdl.handle.net/2263/42470This paper investigates optimization in dynamic environments where the numbers of optima are unknown or fluctuating. The authors present a novel algorithm, Dynamic Population DifferentialEvolution (DynPopDE),which is specifically designed for these problems. DynPopDE is a Differential Evolution based multi-population algorithm that dynamically spawns and removes populations as required. The new algorithm is evaluated on an extension of the Moving Peaks Benchmark. Comparisons with other state-of-the-art algorithms indicate that DynPopDE is an effective approach to use when the number of optima in a dynamic problem space is unknown or changing over time.en© Springer Science+Business Media, LLC. 2012. The original publication is available at : http://link.springer.com/journal/10898.Differential evolutionDynamic environmentsCompeting populationsMoving peaksDynamic number of populationsPostprint Article