ICNPAA 2010: Mathematical Problems in
Engineering, Aerospace and Sciences

Placement of points on a hypersphere according to a pre-specified optimization criterion is an important problem with potential applications ranging from spherical coding theory to computational geometry to defense. Unfortunately, optimal point configurations are known only for a limited number of cases in lower dimensional spaces. Genetic algorithms have been applied to optimal point placement on a 2D sphere. Here, we investigate applications of genetic algorithms to higher dimensional optimization. We utilize minimal energy or maximized minimal inter-point distance optimization criteria, and propose and compare several genetic algorithms crossover and mutation operators.