Fast and flexible genetic algorithm processor

Abstract

In this paper a generic genetic algorithm processor (GAP) with high flexibility in parameter tuning is introduced. The proposed processor utilizes pipeline structure to have low processing time. In order to further increase in the speed, genetic population has been duplicated, one for replacement stage of genetic algorithm (GA) and another for selection phase. Additionally, parallel processing method in the selection stage boosts GA processor's speed. The proposed GA has been designed so that it can work in online controlling circumstances. It supports for constraints in search space and changing environments. Also, a large bit number of chromosomes can be achieved by connecting the proposed 32-bit processors to work as one n-bit chip. Ability to work with two fitness function chips, supporting pipelined fitness functions, and capability of distributed processing are other factors that increase the speed in our design.