TY - JOUR
T1 - Component rationing for available-to-promise scheduling in configure-to-order systems
AU - Chen-Ritzo, Ching Hua
AU - Ervolina, Tom
AU - Harrison, Terry P.
AU - Gupta, Barun
N1 - Funding Information:
The authors thank IBM Integrated Supply Chain and the Center for Supply Chain Research at Penn State University for their generous support of this research. We would also like to extend our gratitude to the Penn State High Performance Computing Group for providing us with excellent computing resources. We thank our reviewers for their many helpful suggestions.
Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2011/5/16
Y1 - 2011/5/16
N2 - We address the problem of rationing common components among multiple products in a configure-to-order system with order configuration uncertainty. The objective of this problem is to maximize expected revenue by implementing a threshold rationing policy. Under this policy, a product is available to promise if fulfilling the order for the product will not cause the inventory of any one of its required components to fall below the component's threshold level for that product. The problem is modeled as a two-stage stochastic integer program and solved using the sample average approximation approach. A heuristic is developed to generate good feasible solutions and lower bound estimates. Using industry data, we examine the benefit of component rationing as compared to a First-Come-First-Served policy and show that this benefit is correlated to the average revenue per product and the variability in the revenue across products whose components are constrained.
AB - We address the problem of rationing common components among multiple products in a configure-to-order system with order configuration uncertainty. The objective of this problem is to maximize expected revenue by implementing a threshold rationing policy. Under this policy, a product is available to promise if fulfilling the order for the product will not cause the inventory of any one of its required components to fall below the component's threshold level for that product. The problem is modeled as a two-stage stochastic integer program and solved using the sample average approximation approach. A heuristic is developed to generate good feasible solutions and lower bound estimates. Using industry data, we examine the benefit of component rationing as compared to a First-Come-First-Served policy and show that this benefit is correlated to the average revenue per product and the variability in the revenue across products whose components are constrained.
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U2 - 10.1016/j.ejor.2010.11.006
DO - 10.1016/j.ejor.2010.11.006
M3 - Article
AN - SCOPUS:79551472966
VL - 211
SP - 57
EP - 65
JO - European Journal of Operational Research
JF - European Journal of Operational Research
SN - 0377-2217
IS - 1
ER -