A hybrid SAGA algorithm for the construction of -optimal cyclic supersaturated designs

In this paper, we propose a hybrid simulated annealing genetic algorithm (SAGA) for generating cyclic structured supersaturated designs. The hybrid SAGA combines features such as the power of the GA and the speed of a local optimizer such as SA, merging the previous metaheuristics into a powerful hybrid optimization algorithm. This class of hybrid metaheuristics enabled us to build supersaturated designs for q = 2 , 3 , … , 14 generators. Comparisons are made with previous works and it is shown that the hybrid SAGA is a powerful tool for the construction of E ( s 2 ) -optimal supersaturated designs.