Performing Different Selection Strategies on Dejong Function

Genetic algorithms are searching and optimization techniques that can be applied in many problems like mathematical optimization and simulation parameterization. Mainly genetic algorithm is used in optimization problems like travelling salesman problem (TSP), dejong function etc. Selection operator is an important operator of genetic algorithm. Selection is a method that randomly picks chromosomes out of the population according to their evaluation function. The higher the fitness function, the more chance an individual has to be selected. In this paper researcher implements various dejong functions (Rastrigin’s function, dejong function1, Axis parallel hyper-ellipsoid) with the help of matlab code. Results are described by the formulation of graphs and tables. The selection technique which is used in the dejong function are roulette wheel selection and rank selection. With these selection schemes results of the dejong functions (Rastrigin’s function, dejong function1,Axis parallel hyper-ellipsoid) are calculated and compared. The aim of this paper is to show the minimum values of dejong function at different generations.