Evolutionary Algorithms (EAs) are search methods that take their inspiration from natural selection and survival of the fittest in the biological world. Genetic Algorithm is a kind of EA GAs emphasize on the behavioral linkage between the parent generation and their offspring. GAs have been successfully applied to many optimization problems in recent years. In this paper, we work with various GA based solutions used to partition a number of objects into a numbers of disjoint subsets according to some problem specific optimization criteria and we also pose the merits and demerits of these solutions. Later on we propose our own structural approach and show the results.