Analysis of Diversity-Preserving Mechanisms for Global Exploration

Tobias Friedrich, Pietro S. Oliveto, Dirk Sudholt, Carsten Witt

    Research output: Contribution to journalJournal articleResearchpeer-review


    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
    Issue number4
    Pages (from-to)455-476
    Publication statusPublished - 2009


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


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