Planning and scheduling are activities of major economic importance. Among various planning and scheduling problems, this paper focuses on the scheduling of crude oil and petroleum derivatives in ports: the jetty scheduling problem. The problem has combinatorial (allocation, sorting) and nonlinear (product blending) aspects, and multi-objective goals (minimization of different costs). We consider problems composed by tankers, tanks, pipelines, and jetties. Simulation models have been used as basis for this formulation. Moreover, real-life instances of the problem are of large scale and, if one wants to solve them in the daily operation of a harbor, they must be solved within minutes in common computer stations. This article proposes an original approach based on a continuous nonlinear optimal control model, without integer (binary) decision variables, which can reduce the problem's size. Numerical experiments are presented using efficient NLP methods, such as LSGRG2, MINOS, and SNOPT

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