In this paper, we address the short-term scheduling of multiproduct batch plants with parallel identical/ nonidentical reactors, a challenging problem that has been motivated by a real-world application at the Dow Chemical Company. The main challenges include handling sequence-dependent changeovers with high variance as well as two-stage production with shared intermediate storage and batch splitting. In order to deal with these issues, we propose a new continuous-time mixed-integer linear programming (MILP) model based oil the concept of asynchronized time slots. The proposed model has the unique feature that it incorporates slot-based mass balances and accounts for sequence-dependent changeovers. While effective for small problems, the proposed model becomes computationally expensive to solve for larger problems, mainly because of the fact that the necessary number of slots is not known a priori and the model requires postulating an upper bound on the slots. Therefore, we propose a bilevel decomposition algorithm in which the original problem is decomposed into all upper-level sequencing and a lower-level scheduling and sequencing problem. The upper-level model is a recent planning model where mass balances are aggregated over-time periods and detailed timing constraints are dropped. However, the effects of changeovers are accounted for by incorporating scheduling constraints. Thus, the upper-level model yields very accurate predictions and a tight upper bound. In the lower level, the original problem is solved for the number of slots and subsets of products as predicted by the upper level, yielding a lower bound. These subproblems are solved iteratively until the bounds converge. In order to reduce the number of total iterations, we propose a new class of symmetry breaking constraints. The application of: the proposed approach is illustrated with several examples.