Fitness Evaluation Expansion to Enhance GA'S Performance in Evolvable Hardware

In this paper the authors introduce a novel experimental method when using genetic algorithms (GAs) to design and optimise digital hardware (HW). This approach proved to enhance the GA's performance. It produced more design solutions than selected comparable techniques used by others and maximises optimisation. The novel aspect of our algorithm works at the fitness evaluation stage, where every single unit's output in the evolved array is taken as a potential solution, instead of specifying specific cells for desired outputs. This will be referred to in this paper as fitness evaluation expansion (FEE). The FEE approach isevaluated experimentally by evolving a 2bit Multiplier and 2bit binary Adder.