Several approaches have been developed into evolutionary algorithms to deal with dynamic optimization problems, of which memory and random immigrants are two major schemes. This pa...
Like Darwinian-type genetic algorithms, there also exists genetic drift in Univariate Marginal Distribution Algorithm (UMDA). Since the universal analysis of genetic drift in UMDA...
We present a genetic model based on simulated recombination of fixed sequences of quaternary genes (assuming four distinct forms, or alleles). States and dynamics of the infinite ...
Estimation of distribution algorithms (EDAs) are widely used in stochastic optimization. Impressive experimental results have been reported in the literature. However, little work ...
This paper investigates how the Univariate Marginal Distribution Algorithm (UMDA) behaves in non-stationary environments when engaging in sampling and selection strategies designe...