The application of mathematical programming techniques is extended to the construction of measurement instruments in generalizability theory. Key concepts in generalizability theory are explained and a description is given of: (1) the one-facet crossed design; (2) the two-facet crossed design; and (3) a two-facet nested design. The optimization of decision studies is also discussed. The current study was undertaken to provide test constructors with procedures to determine the optimal design for measurement instruments with more than one facet. Procedures were developed for two pertinent test construction problems. Chapter 1 is an introduction. Chapter 2 describes the minimization of the number of observations given a minimum acceptable generalizability coefficient. Chapter 3 presents a procedure for the maximization of the generalizability coefficient of a measurement instrument given limited resources. An additional two-step procedure for minimizing the generalizability coefficient under a budget constraint is given in Chapter 4. Chapter 5 offers alternative solutions to maximizing the generalizability coefficient under budget constraints. Chapter 6 addresses the problem of sampling variability of variance components in generalizability theory. The text is in English and a Dutch foreword and abstract are included. Sixty-seven references are included. (SLD)