The research presented in this paper was carried out under the European Community ESPRIT Project HChLOUSO: Hydrocarbon and Chemical Logistics under Uncertainty via Stochastic Optimization. The formulation of a deterministic optimization problem to model logistic operations for a consortium of operators (including AGIP and CLH) was outlined in the CORO model developed by the UITESA and CLH research groups. Here we are proposing an alternative model - DROP: Depot and Refinery Optimization Problem - for strategic or tactical level planning of a company's activities which is based on our understanding of the problem and the technical requirements needed for implementing a stochastic programming formulation. To project random demands for oil products at different locations into the future, and to consider fluctuations in their prices/costs, a stochastic input data simulator has been developed and implemented as a part of our overall modelling system. The research reported here is currently in progress, but in our opinion the complexities of the problem require at this time a detailed report on progress to date. From the viewpoint of the implementation of large stochastic programming models, this work constitutes a case study at the challenging leading edge of the field in that it involves decisions in both space and time in the face of uncertain product demands and prices. This paper treats the specification, generation and solution of the deterministic DROP model in detail. In a companion paper alternative stochastic extensions of this model are studied and a number of novel related research questions and implications are discussed.