Differential evolution for dynamic environments with unknown numbers of optima
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Date
Authors
Du Plessis, M.C. (Mathys Cornelius)
Engelbrecht, Andries P.
Journal Title
Journal ISSN
Volume Title
Publisher
Springer
Abstract
This 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.
Description
Keywords
Differential evolution, Dynamic environments, Competing populations, Moving peaks, Dynamic number of populations
Sustainable Development Goals
Citation
Du 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.