A modified steady state genetic algorithm suitable for fast pipelined hardware

Abstract

In this paper, a modification of steady state genetic algorithm, called dual-population scheme, is proposed to improve its execution speed on electronic hardware. It utilizes two memories to store two interactive populations on them. The system, inherently interchanges chromosomes between these populations. In this manner, it can fully benefit from the pipeline processing on hardware. It is shown that the proposed method performs much faster than the standard steady state and canonical genetic algorithms on pipelined genetic hardware. Moreover, the searching performance, repeatability and convergence properties of the proposed technique were tested. They show dual-population scheme performs similarly to the regular genetic algorithms while achieves better results than the present hardware-oriented genetic algorithm models.