The challenging structure as well as the extensive economical potential of solving various scheduling problems has fascinated numerous researchers during the recent decades. Despite the significant progress made in the fields of operations research and process systems engineering (Puigjaner, Comp. Chem. Eng., 23 (1999): S929-S943; Shah, Proceedings of FOCAPO'98, Snowbird, Utah, USA, 1998) the complexity of many industrial-size scheduling problems means that a global optimal solution cannot be reached within a reasonable computational time. In these cases, the production schedule must be generated using e.g. some kind of sophisticated heuristics, which can often lead to suboptimal solutions. In this paper, we introduce a Mixed Integer Linear Programming (MILP) based algorithm, which can be efficiently used to improve an existing feasible, but non-optimal, production schedule or to reschedule jobs in the case of changed operational parameters. The algorithm has been successfully applied to certain scheduling problems in both the paper-converting and pharmaceutical industry.