Once the genetic representation and the fitness function are defined , a GA proceeds to initialize a population of solutions and then to improve it through repetitive application of the mutation , crossover , inversion and selection operators .
Once a genetic representation and fitness function are defined , a genetic algorithm will instantiate initial candidates as described previously , and then improve through repetitive application of mutation , crossover , inversion and selection operators ( as defined according to the problem domain ) .