ABSTRACT
A number of biology-inspired models of computing evolved out of the enterprise. One such model is genetic algorithms (GAs). This chapter discusses abstract mathematical models of natural genetics and the process of biological evolution—models that are capable of solving difficult problems. The mimicking algorithm has become known as GA—a simplified mathematical model of what nature does in genetics and evolution. GAs have been extensively and most successfully exploited in the calculation of energy and prediction of structures of atomic/molecular clusters. The M. D. Vose and G. E. Liepins theory examines the dynamics of evolution of the population in a GA under the action of genetic operators on strings. The dynamics are examined in order to understand how the GA moves the population from one point on the relevant surface to another, and ascertains when the GA dynamics remains stable.
