Supply chain planning: using simulation to evaluate buffer adjustment methods in order promising

Authors:
Hank Grant;Scott Moses;Dave Goldsman
Affiliations:
University of Oklahoma, Norman, OK;University of Oklahoma, Norman, OK;Georgia Institute of Technology, Atlanta, GA
Venue:
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
Year:
2002

Citing 10
Cited 1

Setting planned leadtimes in serial production systems with tardiness costs

Management Science
Due-date setting and priority sequencing in a multiclass M/G.1 queue

Management Science
Scheduling real-time transactions: a performance evaluation

ACM Transactions on Database Systems (TODS)
A broader view of the job-shop scheduling problem

Management Science
Due-date assignment to multi-job customer orders

Management Science
Single facility due date setting with multiple customer classes

Management Science
Quoting customer lead times

Management Science
Effects of deadline propagation on scheduling nested transactions in distributed real-time database systems

Information Systems - Special issue on real-time database systems
Database research at the University of Oklahoma

ACM SIGMOD Record
Simulation with Visual Slam and Awesim

Simulation with Visual Slam and Awesim

Real-time prediction of order flowtimes using support vector regression

Computers and Operations Research

Quantified Score

Hi-index	0.00

Visualization

Abstract

Much literature exists for scheduling production, but there is little work on establishing the due dates that serve as the inputs to developing a production schedule. We call this Order Promising. This paper explores a simulation-based approach for evaluating methods for promising the delivery of orders based on dynamic buffer adjustment coupled with various methods to forecast the amount of buffer required. The primary objective of the paper is to frame the problem and suggest methods of analysis. Preliminary computational results are also presented.