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|Title:||Ensemble differential evolution with dynamic subpopulations and adaptive clearing for solving dynamic optimization problems||Authors:||Suganthan, P. N.
|Keywords:||DRNTU::Engineering::Electrical and electronic engineering||Issue Date:||2012||Source:||Hui, 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).||Abstract:||Many 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.||URI:||https://hdl.handle.net/10356/84643
|DOI:||http://dx.doi.org/10.1109/CEC.2012.6252866||Rights:||© 2012 IEEE.||Fulltext Permission:||none||Fulltext Availability:||No Fulltext|
|Appears in Collections:||EEE Conference Papers|
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