  In many publications, authors showed that chaotic pseudo random number
generators (PRNGs) may improve performance of the evolutionary algorithms. In
this paper, we use two chaotic maps Gingerbread man and Tinkerbell as the
chaotic PRNGs instead of the classical PRNG in the differential evolution.
Numbers generated by this maps are normalized to the unit interval by three
different methods -- operation modulo, straightforward number normalization
where we know minimal and maximal generated number and arctangent of the two
variables $x$ and $y$, where numbers $x$ and $y$ are generated by the
Gingerbread man map and Tinkerbell map. The first goal of this paper is to show
whether the differential evolution convergence speed might be affected by the
way how we normalize number generated by the chaotic map. The second goal is to
find out the influence of the probability distribution function of the selected
chaotic PRNGs. The results mentioned below showed that the selected
normalization method may improve differential evolution convergence speed,
especially in the case of arctangent and straightforward number normalization,
where we know the minimal and maximal generated numbers.
