Optimization of fractal : function using genetic algorithms
Abstract
In this work, we investigate the difficult problem of the optimization of fractal functions. We first derive some relations between the local scaling exponents of the functions, the sampling rate and the accuracy of the localization of the optimum, both in the domain and the range of the functions. We then apply these ideas to the resolution of the inverse problem for iterated function system (IFS) using a genetic algorithm. In the conditions of study (2D problem for sets), the optimization process yields the optimum with a good precision and within a tractable computing time.