In a generational genetic algorithm, at each generation, the entire population is replaced by offspring produced via selection, crossover, and mutation.
Basically, evolution proceeds in discrete generations, such that parents are discarded after producing offspring; the new generation is componsed entirely of new individuals.
We can consider the Simple Genetic Algorithm to be a specific instantiation of a generational GA; it assumes fixed-length encoding, fitness-proportional selection, standard crossover, mutation, and full replacement. Thus, GGA is a broader class than SGA.
