Lot Streaming in Job-Shop Scheduling

• Published in: Operations research Vol. 45; no. 4; pp. 584 - 595
• Main Authors: Dauzere-Peres, Stephane, Lasserre, Jean-Bernard
• Format: Journal Article
• Language: English
• Published: Linthicum, MD INFORMS 01.07.1997; Operations Research Society of America; Institute for Operations Research and the Management Sciences
• Subjects: Applied sciences; Economic models; Exact sciences and technology; Experimental procedures; Heuristics; Iterative solutions; Job shops; Linear programming; lot streaming; Mathematical models; Operational research and scientific management; Operational research. Management science; Operations research; Optimal solutions; Perceptron convergence procedure; Production scheduling; Scheduling; Scheduling, sequencing; Sequencing; Streaming; Studies; Lower bound; Test; Job shop; Flow shop; Scheduling; Lot sizing; Makespan
• ISSN: 0030-364X; 1526-5463
• DOI: 10.1287/opre.45.4.584

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.