3 papers
cs.NE2026
A restart rule for genetic algorithms based on Schnabel census
Anton Eremeev, Yulia Zakharova
A new adaptive restart rule for Genetic Algorithms (GAs) is considered. The rule is based on the Schnabel Census method, originally developed for statistical estimation of a size o…
cs.NE2026
Asymptotical Analysis of the GA Escape Time from Local Optima on Jump Functions
Anton V. Eremeev, Valentin A. Topchii
The paper develops the approach to the runtime analysis of evolutionary algorithms on the basis of limit theorems from probability theory. We consider the family of Jump benchm…
cs.NE2026
Generalized Heavy-tailed Mutation for Evolutionary Algorithms
Anton V. Eremeev, Dmitri V. Silaev, Valentin A. Topchii
The heavy-tailed mutation operator, proposed by Doerr, Le, Makhmara, and Nguyen (2017) for evolutionary algorithms, is based on the power-law assumption of mutation rate distributi…