A genetic algorithm comes with many variants depending on the operator being used for the solution of a target problem. Typical types of operators include crossover, mutation and selection implementations (e.g. roulette wheel technique). All these are methods of selecting the best possible individual from a population of individuals in order to create a new offspring. At this point, the fitness of this offspring can be calculated and if certain circumstances are not met, then a reinsertion mechanism has also to be applied. Reinsertion deals with the replacement of specific only parents in order to redetermine the individuals of the created population. The used selection method (operator) is the one that determines the reinsertion technique!!!
A genetic algorithm comes with many variants depending on the operator being used for the solution of a target problem. Typical types of operators include crossover, mutation and selection implementations (e.g. roulette wheel technique). All these are methods of selecting the best possible individual from a population of individuals in order to create a new offspring. At this point, the fitness of this offspring can be calculated and if certain circumstances are not met, then a reinsertion mechanism has also to be applied. Reinsertion deals with the replacement of specific only parents in order to redetermine the individuals of the created population. The used selection method (operator) is the one that determines the reinsertion technique!!!