This paper presents a new multiple-time-grid, continuous-time mixed-integer linear program (MILP) model for the short-term scheduling of multistage, multiproduct plants. It can handle both release and due dates and different objective functions efficiently, such as the minimization of total cost, total earliness, or makespan. This formulation is compared to other existing mixed-integer linear programming approaches and to a constraint-programming model. The results show that the proposed formulation is much more efficient than its uniform-time-grid counterpart and is comparable to a continuous-time formulation that uses global precedence sequencing variables. Discrete-time formulations are preferred for larger scheduling problems where a reasonable number of time points are sufficient for the exact problem data. The results also show that the constraint-programming model is the best approach for makespan minimization.