Due date management

Bagchi, U., Sullivan, R.S. and Chang, Y.L., 1987. Minimizing mean square deviation of completion times about a common due date. Management Sciences, 33, 894-906. Baker, K.R. and Scudder, G.D., 1990. Sequencing with earliness and tardiness penalties a review. Operations Research, 38(1), 22-36. 

P. Keskinocak and S. Tayur. Due date management policies. In Supply Chain Analysis in the eBusiness Era. Kluwer, 2002. 

There are several dimensions that distinguish different due date management problems. Depending on the system (i.e., the manufacturing or service organization) under consideration, a combination of these dimensions will be present and this combination will affect the appropriate mathematical model for studying DDM in that setting. 

To study the effectiveness of due date management policies, three approaches are used simulation, analytical methods and competitive analysis. While they are quite interesting from a theoretical perspective, the application of analytical models to DDM has been mostly limited to simple settings, such as special cases of offline single machine problems. To study the effect of DDM policies in more realistic multi-machine environments where orders arrive over time, researchers have commonly turned to simulation. 

In the remaining part of this section, we discuss the papers with online DDM models in more detail. We use the term machine to refer to any type of resource. We say that due date management policy A dominates B, if both policies satisfy the same service level constraints and policy A achieves a better objective function than policy B. 

Few researchers have studied the impact of product structures on flow times, scheduling and due date management policies [41] [56]. For assembly jobs, delays in the system occur not only due to waiting in queues (due to busy resources), but also due to staging, i.e., waiting for the completion of other parts of the job before assembly. Fry et al. [41] study the impact of the following job parameters on the flow time total processing time (sum of all operation... 

The first two of these rules are parametric and the parameters a and (3 are chosen (based on simulation experiments) such that the service level constraints are satisfied. These rules apply to both problems I and II. The third and fourth rules set the shortest possible due date at any time to satisfy the service level constraints of the maximum fraction of tardy jobs and the maximum average tardiness, and apply to problems I and II, respectively. The proposed due date management policies use these rules with SPT sequencing between different classes, and FCFS sequencing within each class. 

Due Date Management with Price and Order Selection Decisions... 

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