Genetic Algorithms in Optimization

Genetic algorithms (GAS) are iterative processes for finding good solutions to optimization problems. GAS operate on a population of individuals which represents a set of potential solutions to a given problem. We usually think of such a population at a particular iterate (or step) as a generation. From each generation, a set of good individuals (corresponding to good solutions) is selected to mate to produce a new generation. Since the selection process favors good individuals (i.e., more copies of them are selected for mating than others), the quality of the subsequent generations will gradually improve and eventually approach optimality, much like the way life forms evolve with survival of the fittest.