PPSN - Parallel Problem Solving from Nature

Abstract

We study an evolutionary algorithm used for optimizing in a chaotically changing dynamic environment. The corresponding chaotic non–stationary fitness landscape can be characterized by quantifiers of the underlying dynamics–generating system. We give experimental re- sults about how these quantifiers, namely the Lyapunov exponents, to- gether with the environmental change period of the landscape influence performance measures of the evolutionary algorithm used for tracking optima.