Nowadays, the development of global competition has been one of the main factors that have driven the efforts toward the optimisation development. Therefore, oil refineries have been encouraged to be restructured for competing successfully in this new scenario with low profit margin, tighter environmental regulations and more efficient plant operation. However, many years and a lot of human and computational efforts have been dedicated to improve the techniques applied for the overall refinery optimisation. Good developments have come successfully operating at the planning level; but developing and solving rigorous overall plant optimisation models at the production scheduling level still are at research stage and much more work must be done to continue improving in this field through the involvement of difficult tasks due to the mathematical complexity of the models which have the compulsory use of a large quantity of equations and variables that hugely increase the size of the problem. This Thesis presents a new generic mixed integer linear programming model for optimising the scheduling of crude oil unloading, inventories, blending and feed to oil refineries that usually unload several kinds of crude oils with different compositions. The objective function of the model consists on minimising the operational cost generated during the mentioned operation. Case studies are presented and compared each other illustrating the capabilities of the model to solve operation scheduling problems in this area and to support future expansion projects for the system as they happen in real situations. The solution involves optimal operation of crude oil unloading, optimal transfer rates among equipments in accordance with the pumping capacities and tank volume limitations, optimal oscillation of crude oil blended compositions and fulfilment of the oil charging demand per process unit. border’s fringe.