Comparative study of different selection techniques in genetic algorithm

Genetic Algorithm is search and optimization technique which has number of steps like initialization, selection, crossover, mutation and replacement. Genetic algorithms are optimization search algorithms that maximize or minimizes given functions. Since GA is heuristic procedures, they are not guaranteed to find the optimum, but experience has shown that they are able to find very good solutions for a wide range of problems. In this paper focus is given on selection phase of GA and comparison between different selection techniques of GA. In selection operator individual are selected according to their fitness and chooses those chromosomes in the population that will be allowed to reproduce, and on average the fitter chromosomes produce more offspring than the less fit ones. Researcher has done lot of work in selection phase of GA. In this paper a number of selection techniques have been described like roulette wheel selection, rank selection, tournament selection, steady state selection, Boltzmann selection and Elitism selection.