A typical front-end crude supply process of refineries encompasses many units, such as vessels, port-side storage tanks, long-distance pipeline, refinery-side charging tanks, and crude distillation units. In reality, the performance of these units will inevitably decay; thus, unit maintenance plans should be well integrated with normal crude movement schedules. In this paper, a novel methodology has been proposed to dynamically and simultaneously determine the optimal schedule of crude movement and unit maintenance operations. Specifically, both proactive scheduling for multiple preventive maintenance tasks and reactive scheduling for emergent corrective maintenance tasks are systematically integrated. Accordingly, the developed mixed-integer nonlinear programming (MINLP) model will optimize the operation schedule for the front-end crude supply process via minimizing the total operating cost during the scheduling time horizon. Meanwhile, it can also determine the optimal unit maintenance schedule, which will identify the best opportunities of not only isolating units from process system to perform maintenance but also resuming their services after maintenance. The model can simultaneously handle multiple unit maintenance tasks while satisfying all strict constraints for crude transferring, storing, blending, and processing operations. The efficacy of the developed methodology and the MINLP model has been demonstrated through various case studies.