However, since this method needs to compare all the semijoin sequence programs, it results in a high computation effort. However, five percent of a search space in complex queries still represents a substantial computational effort. According to the evolution theory of Darwin, biological structures that are more successful in grappling with their environment survive and reproduce at a higher rate. This principle is used in Evolutionary Algorithms, for which Genetic Algorithms and Genetic Programming are two of its major classes. Three processes, namely, selection , crossover , and mutation are applied to the string populations to create new ones.
Reproduction takes place on a single chromosome and allows fitter chromosomes to reproduce more.
Crossover, the sexual recombination, creates different chromosomes in the offspring by combining materials from the chromosomes of the two parents. Mutation causes the chromosomes of biological offspring to be different from those of their biological parents. The structures undergoing adaptation in GP are a population of individual computer programs from the search space. These computer programs are generally hierarchically organized and of dynamically varying size and shape. In our case, an individual consists of a specific sequence of semijoin operations.