Continuous-Time Formulation for Integrated Refinery Planning and Diesel Blending Scheduling Problems

In the decision-making process, planning and scheduling tools often present conflicting schemes due to discrepancies in precision levels, leading to challenges in actual manufacturing processes. This contradiction arises from the differing precisions between planning and scheduling models. The continuous-time planning representation proposed in this work offers greater flexibility compared to conventional discrete-time methods, particularly in handling varying delivery demands. A mixed-integer nonlinear programming (MINLP) formulation incorporating continuous-time representation is proposed to address the integrated refinery planning and diesel blending scheduling problem in this study. A bilevel strategy is implemented to efficiently prune certain integer branches, expediting the solution process. A calculation study is explored to evaluate the performance of the proposed model in comparison with conventional approaches, striking a balance between feasibility and solution efficiency. The findings suggest potential avenues for the enhancement of plant-wide planning and scheduling processes.