Classical Approaches of Genetic Algorithms and Their Suitability

Abstract

Genetic algorithms derived from observations of nature and simulation of artificial selection of organisms with multiple loci that control a measurable trait. To date, genetic algorithms evolved into complex and strong informatics tools able to deal with hard problems of decision, classification, optimization and simulation. A series of studies reported biotechnology hard problems solved using genetic algorithms. In this context, the aim of the present article is to introduce genetic algorithms and to present their suitability for biotechnology hard problems. Impor-tant results are reported in the available literature that deal with the application of genetic algorithms for biotechnology process modelling.