THE INFLUENCE OF STOCHASTIC QUALITY FUNCTIONS ON EVOLUTIONARY SEARCH

In this chapter, we will analyse the influence of noise on the search behaviour of evolutionary algorithms. We will introduce different classes of functions which go beyond the simple additive noise model. The first function demonstrates a trade-off between an expectation and a variance based measure for the evaluation of the quality in the context of stochastic optimisation problems. Thereafter, we concentrate on functions whose topology is changed when the expectation value is taken as the quality criterion. In particular, for functions with noise induced multi-modality (FNIM), the process can be regarded as a bifurcation. The behaviour of two types of evolution strategies is analysed for FNIMs.