A study on sampling errors of variance components was conducted within the framework of generalizability theory by P. L. Smith (1978). The study used an intuitive approach for solving the problem of how to allocate the number of conditions to different facets in order to produce the most stable estimate of the universe score variance. Optimization techniques are proposed as a promising approach for solving allocation problems in generalizability studies. An important consequence of the conclusion that allocation problems in generalizability studies have much in common with allocation problems in decision studies would be a considerable reduction in the effort required to develop optimization procedures and computer programs. This examination of optimization techniques is the beginning of a procedure that enables the researcher to design a generalizability study in line with stated limits on sampling errors as well as resources. (SLD)