A problem-specific model is presented for the short-term scheduling problem in the Fast Moving Consumer Goods (FMCG) industry. To increase the computational efficiency, the limited intermediate inventory is modeled indirectly by relating mixing and packing intervals. In addition, the model size is reduced by exploiting the process characteristics by dedicating time intervals to product types. The efficiency and flexibility of the formulation is demonstrated using ten examples based on an ice cream scheduling case study. The examples contain 62-73 batches of 8 products that must be produced within a 120-h horizon. All cases can be solved to optimality within 170 s. The addition of a periodic cleaning requirement on the mixing lines significantly increases the complexity of the problem. An algorithm is proposed that solves to optimality within half an hour 9 out of 10 cases with periodic cleaning. For the 10th case the makespan obtained was 0.6% higher than the theoretical minimum makespan.