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dc.contributor.authorSuganthan, P. N.en
dc.contributor.authorSheldon Hui.en
dc.identifier.citationHui, S., & Suganthan, P. N. (2012). Ensemble Differential Evolution with dynamic subpopulations and adaptive clearing for solving dynamic optimization problems. 2012 IEEE Congress on Evolutionary Computation (CEC).en
dc.description.abstractMany real-life optimization problems are dynamic in time, demanding optimization algorithms to perform search for the best solutions in a time-varying problem space. Among population-based Evolutionary Algorithms (EAs), Differential Evolution (DE) is a simple but highly effective method that has been successfully applied to a wide variety of problems. We propose a technique to solve dynamic optimization problems (DOPs) using a multi-population version of DE that incorporates an ensemble of adaptive mutation strategies with a greedy tournament global search method, as well as keeps track of past good solutions in an archive with adaptive clearing to enhance population diversity.en
dc.rights© 2012 IEEE.en
dc.subjectDRNTU::Engineering::Electrical and electronic engineeringen
dc.titleEnsemble differential evolution with dynamic subpopulations and adaptive clearing for solving dynamic optimization problemsen
dc.typeConference Paperen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen
dc.contributor.conferenceIEEE Congress on Evolutionary Computation (2012 : Brisbane, Australia)en
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