This paper presents a lens system design algorithm using the covariance matrix adaptation evolution strategy (CMA-ES), which is one of the most powerful self-adaptation mechanisms. The lens design problem is a very difficult optimization problem because the typical search space is a complicated multidimensional space including many local optima, non-linearities, and strongly correlated paramete...

NK landscapes (NKL) are stochastically generated pseudoboolean functions with N bits (genes) and K interactions between genes. By means of the parameter K ruggedness as well as the epistasis can be controlled. NKL are particularly useful to understand the dynamics of evolutionary search. We extend NKL from the traditional binary case to a mixed variable case with continuous, nominal discrete, a...

The family of natural evolution strategies (NES) offers a principled approach to real-valued evolutionary optimization by following the natural gradient of the expected fitness on the parameters of its search distribution. While general in its formulation, existing research has focused only on multivariate Gaussian search distributions. We address this shortcoming by exhibiting problem classes ...

Several modified particle swarm optimizers are proposed in this paper. In DVPSO, a distribution vector is used in the update of velocity. This vector is adjusted automatically according to the distribution of particles in each dimension. In COPSO, the probabilistic use of a ‘crossing over’ update is introduced to escape from local minima. The landscape adaptive particle swarm optimizer (LAPSO) ...

1 Abstract— With the increasing number of intrusions in systems' and networks' infrastructures, Intrusion Detection Systems (IDS) have become an active area of research to develop reliable and effective solutions to detect and counter them. The use of Evolutionary Algorithms in IDS has proved its maturity over the times. Although most of the research works have been based on the use of genetic ...