Evolutionary systems are a kind of system, which reproduce with mutation whereby the foremost fit elements survive, and therefore the less fit die down. One among the developers of the evolutionary systems thinking is Béla H. Bánáthy. Evolutionary systems are characterized by "moving equilibria and therefore the dynamics of coevolutionary interactions which may not be foreseen ex ante." The study of evolutionary systems is a crucial subcategory of Complex Systems research. Biological evolution as conceived by this synthetic theory of evolution is modelled by a mathematical system which consists of three arrays: the genotype and phenotype population and their environment, and 4 operators: selection, mutation, recombination, and alteration (describing the change of the environment by the population). An evolutionary process then might be represented because the cyclic iteration of those operations on the respective arrays. Some simple versions of this technique were investigated by simulation. They exhibited the subsequent properties. (i) Population fitness increased with the generation number. (ii) The evolutionary rate increased with variance of fitness. (iii) The evolutionary rate increased with the amount of people, and decreased with the amount of loci. (iv) The evolutionary rate increased with the choice pressure. (v) For a given system during a given state there existed an optimal mutation rate. (vi) Free recombination was optimal. (vii) The mutational load of fitness increased with the mutation rate, but was independent of the choice pressure; contrary to the present, the mutational load of the population “morph” decreased with the choice pressure, i.e. one could catch up on the deleterious effect of mutation by strong selection.