In large refineries, the resource-oriented plan of crude oil is commonly required to be tractable and decomposable for practical operation scheduling, especially for large-scale scheduling. To this end, a framework of hybrid optimization based on plan decomposition (FHO/PD) is proposed, which mainly depends on evolutionary algorithms to realize the flexible decomposition from large-scale planning to scheduling and takes advantage of mathematical programming to improve the solving efficiency synchronously. Finally, the experimental results on a practical case suggest that the proposed method has shown great flexibility and applicability in crude oil scheduling.