AbstractThis paper describes the application of a linear programming model to project selection and resource allocation problems in two industrial R&D laboratories. Mathematical models have not been widely used in practice because of the inherent uncertainty of research. The model discussed here yields information about the outcome of decisions under conditions of uncertainty. The elements of the model are developed, using simple examples, and the form of the complete model outlined. Benefit evaluation is carried out using probabilistic networks and uncertainty in benefits included by utilizing the concept of certainty equivalence. The use of the model in practical situations is discussed, with examples of the information obtained from the solution, and sensitivity studies to investigate the uncertain environment are described. The result is a flexible model, which produces information necessary for planning purposes and which is acceptable to practising R&D Managers.