Optimizing the monthly scheduling of crudes in a terminal-refinery system

This paper focuses on solving the optimization of crude oil operations scheduling carried out in a real system composed of a refinery and a marine terminal, over a monthly horizon. In the present article, we introduce a large-scale mixed-integer non-linear programming (MINLP) model that faithfully represents the operation and characteristics of the system. Considering the model's complexity and its non-linear and non-convex nature, the challenge lies in solving the model in a time frame that meets the user's needs. To tackle this problem, we develop a temporal decomposition method in conjunction with a linear approximation. Copyright (c) 2023 The Authors.