Comparison of independent, stratified and random covering sample schemes in optimization problems

We consider two schemes of global optimization algorithms based on the use of grids. Our main goal is to compare the so-called independent sampling (IS), stratified sampling (SS) and random covering (RC) grids implemented to the estimation problem of the global maximum of a function. The results give an insight on how a decrease of randomness in selection rules for the trial points improves efficiency of global random search algorithms.