— We present the memetic climber, a simple search algorithm that learns topology and weights of neural networks on different time scales. When applied to the problem of learning ...
We introduce the Spacing Memetic Algorithm (SMA), a formal evolutionary model devoted to a systematic control of spacing (distances) among individuals. SMA uses search space dista...
Daniel Cosmin Porumbel, Jin-Kao Hao, Pascale Kuntz
Genetic algorithms are a population-based Meta heuristics. They have been successfully applied to many optimization problems. However, premature convergence is an inherent charact...
A Quasi-Monte-Carlo method based on the computation of a surrogate model of the fitness function is proposed, and its convergence at super-linear rate 3/2 is proved under rather ...
In combinatorial solution spaces Iterated Local Search (ILS) turns out to be exceptionally successful. The question arises: is ILS also capable of improving the optimization proces...