A batch splitting heuristic for dynamic job shop scheduling problem

The job shop scheduling problem has been a major target for many researchers. Unfortunately, though, most of the past studies assumed that a job consists of only a single part. If we assume that a job consists of a batch as in many real manufacturing environment, then we can obtain an improved schedule. However, then, the size of the scheduling problem would become too large to be solved in practical time limit. So, we proposed an algorithm to get an improved schedule by splitting the original batch into smaller batches, and thereby can meet the due date requirement, and adapt to unexpected dynamic events such as machine failure, rush order and expediting.