37 citations · 140 across the 33 of their papers we have counts for
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cs.NE2016★ 1 cited
Escaping Local Optima using Crossover with Emergent or Reinforced Diversity
Duc-Cuong Dang, Tobias Friedrich, Timo Kötzing +5
Population diversity is essential for avoiding premature convergence in Genetic Algorithms (GAs) and for the effective use of crossover. Yet the dynamics of how diversity emerges i…
cs.NE2016★ 9 cited
Update Strength in EDAs and ACO: How to Avoid Genetic Drift
Dirk Sudholt, Carsten Witt
We provide a rigorous runtime analysis concerning the update strength, a vital parameter in probabilistic model-building GAs such as the step size in the compact Genetic Algo…