Lot Streaming in Job-Shop Scheduling

The issue in Lot Streaming is how to split lots into sublots in order to improve the makespan (or some other criterion). We present a model and an iterative procedure for a general job-shop environment. The procedure alternates between solving a lot-sizing problem with a given sequence of sublots on the machines, and a standard job-shop scheduling problem with fixed sublot sizes. We report the computational results on a significant sample of 120 job-shop and flow-shop scheduling problems (including the famous 10–10). In case of no setup, in a few iterations, the makespan approaches a lower bound using very few sublots, suggesting that the procedure yields a global optimum. As a by-product, this result somehow validates the capacitated lot-sizing models in which the detailed capacity constraints, induced by the sequencing of operations, are ignored.