Extended study on the randomization and sequencing for the chaos embedded heuristic

Abstract

This research deals with the hybridization of two soft-computing fields, which are chaos theory and evolutionary algorithms. This paper investigates the utilization of the time-continuous chaotic system, which is Ueda oscillator, as the chaotic pseudo random number generator (CPRNG) embedded into the selected heuristics. Through the utilization of time-continuous systems and with different sampling times from very small to bigger, it is possible to fully keep, suppress or remove the hidden complex chaotic dynamics from the generated pseudo random data series. Repeated simulations were performed investigating the influence of the oscillator sampling time to the selected heuristic, which is differential evolution algorithm (DE). Experiments are focused on the extended investigation, whether the different randomization and pseudo random numbers distribution given by particular CPRNG or hidden complex chaotic dynamics providing the unique sequencing are beneficial to the heuristic performance. This research utilizes set of 4 selected benchmark functions, three different sampling rates of Ueda oscillator; further results are compared against canonical DE.