Evolving building blocks for genetic algorithms using genetic engineering

We present a modification to the standard genetic algorithm (GA), which is based on concepts of genetic engineering. The motivation is to discover useful and harmful genetic materials and then execute an evolution process in such a way that the population becomes increasingly composed of useful genetic material and increasingly free of the harmful genetic material. Compared to the standard GA it provides some computational advantages as well as a tool for automatic generation of the genetic representations which are specifically tailored to suit certain classes of problems