Analysis of Diversity-Preserving Mechanisms for Global Exploration

Publication: Research - peer-reviewJournal article – Annual report year: 2009

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Maintaining diversity is important for the performance of evolutionary algorithms. Diversity-preserving mechanisms can enhance global exploration of the search space and enable crossover to find dissimilar individuals for recombination. We focus on the global exploration capabilities of mutation-based algorithms. Using a simple bimodal test function and rigorous runtime analyses, we compare well-known diversity-preserving mechanisms like deterministic crowding, fitness sharing, and others with a plain algorithm without diversification. We show that diversification is necessary for global exploration, but not all mechanisms succeed in finding both optima efficiently. Our theoretical results are accompanied by additional experiments for different population sizes.
Original languageEnglish
JournalEvolutionary Computation
Publication date2009
Volume17
Issue4
Pages455-476
ISSN1063-6560
DOIs
StatePublished
CitationsWeb of Science® Times Cited: 10

Keywords

  • Diversity, Runtime analysis, Fitness sharing, Deterministic crowding, Exploration
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