Intelligent production planning and scheduling are of paramount importance to ensure refinery profitability, logistic reliability and safety at the local and corporate levels. In Brazil, such activities play a particularly critical role, since the Brazilian downstream model is moving towards a demand-driven model rather than a supply-driven one. Moreover, new and specialized non-linear constraints are continuously being incorporated into these large-scale problems: increases in oil prices implying the need for processing poor quality crudes, increasing demand and new demand patterns for petroleum products, new stringent environmental regulations related to clean fuels and start-up of new production technologies embedded into more complex refining schemes. This paper aims at clarifying the central role of refinery planning and scheduling activities in the Petrobras refining business. Major past and present results are outlined and corporate long-term strategies to deal with present and future challenges are presented.

The objective of this paper is the development and solution of nonlinear and mixed-integer (MIP) optimization models for real-world planning and scheduling problems in petroleum refineries. Firstly, we present a nonlinear planning model that represents a general refinery topology and allows implementation of nonlinear process models as well as blending relations. The optimization model is able to define new operating points, thus increasing the production of the more valuable products and simultaneously satisfying all specification constraints. The second part addresses scheduling problems in oil refineries, which are formulated as MIP optimization models and rely on both continuous and discrete time representations. Three practical applications closely related to the current refinery scenario are presented. The first one addresses the problem of crude oil inventory management of a refinery that receives several types of crude oil delivered exclusively by a single oil pipeline. Subsequently, two optimization models intended to define the optimal production policy, inventory control and distribution are proposed and solved for the fuel oil and asphalt plant. Finally, the planning model of Moro et al. (1998) is extended in order to sequence decisions at the scheduling level in the liquefied petroleum gas (LPG) area for maximization of the production of petrochemical-grade propane and product delivery.