title: Genetic algorithms: principles of natural selection applied to computation.
abstract: A genetic algorithm is a form of evolution that occurs on a computer. Genetic algorithms are a search method that can be used for both solving problems and modeling evolutionary systems. With various mapping techniques and an appropriate measure of fitness, a genetic algorithm can be tailored to evolve a solution for many types of problems, including optimization of a function of determination of the proper order of a sequence. Mathematical analysis has begun to explain how genetic algorithms work and how best to use them. Recently, genetic algorithms have been used to model several natural evolutionary systems, including immune systems.
authors.affiliation: Department of Computer Science, University of New Mexico, Albuquerque 87131-1386.
authors.forename: S
authors.initials: S
authors.lastname: Forrest
mesh_terms: D000465:Algorithms; D000917:Antibody Formation; D005075:Biological Evolution; D003198:Computer Simulation; D004463:Ecology; D005803:Genes, Immunoglobulin; D007135:Immunoglobulin Variable Region / Q000235:genetics; D012984:Software
chemical_list: D007135:Immunoglobulin Variable Region