Abstract
AbstractThe Age-Layered Population Structure (ALPS) paradigm is a novel metaheuristic for overcoming premature convergence by running multiple instances of a search algorithm simultaneously. When the ALPS paradigm was first introduced it was combined with a generational Evolutionary Algorithm (EA) and the ALPS-EA was shown to work significantly better than a basic EA. Here we describe a version of ALPS with a steady-state EA, which is well suited for use in situations in which the synchronization constraints of a generational model are not desired. To demonstrate the effectiveness of our version of ALPS we compare it against a basic steady-state EA (BEA) in two test problems and find that it outperforms the BEA in both cases.KeywordsAgeEvolutionary DesignGenetic ProgrammingMetaheuristicPremature Convergence
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