Effects of Selection & Scaling strategies on the performance of GA

One of the most important things in Genetic Algorithm is to control the bias of the algorithm towards high-quality solutions in such a way that preserves the diversity in the population, and prevents premature convergence. Certain manipulations are usually essential to speed up and improve the Genetic Algorithm performance. Among those manipulations are the fitness scaling strategies and selection schemes. The implementation of these methods, comparison between these methods are presented in this work. The discussion of their effects on the performance of Genetic Algorithm are also illustrated.