tThis paper considers a dairy industry problem on integrated planning and scheduling of set yoghurtproduction. A mixed integer linear programming formulation is introduced to integrate tactical andoperational decisions and a heuristic approach is proposed to decompose time buckets of the decisions.The decomposition heuristic improves computational efficiency by solving big bucket planning and smallbucket scheduling problems. Further, mixed integer linear programming and constraint programmingmethodologies are combined with the algorithm to show their complementary strengths. Numericalstudies using illustrative data with high demand granularity (i.e., a large number of small-sized customerorders) demonstrate that the proposed decomposition heuristic has consistent results minimizing thetotal cost (i.e., on average 8.75% gap with the best lower bound value found by MILP) and, the developedhybrid approach is capable of solving real sized instances within a reasonable amount of time (i.e., onaverage 92% faster than MILP in CPU time).