Diversifying exploration of features spaces in evolutionary searches

Evolutionary algorithms require excellent search capabilities in order to find global minima, particularly in complex feature spaces. A means of enhancing search capabilities based upon a distributed genetic-style encoding of solution has been shown to be advantageous. Such a representation requires the use of varying gene lengths. The effects of variable gene lengths are explored in detail