Sales and operations planning in systems with order configuration uncertainty

Ching Hua Chen-Ritzo, Tom Ervolina, Terry Paul Harrison, Barun Gupta

Research output: Contribution to journalArticle

22 Scopus citations

Abstract

This paper addresses the problem of aligning demand and supply in configure-to-order systems. Using stochastic programming methods, this study demonstrates the value of accounting for the uncertainty associated with how orders are configured. We also demonstrate the value of component supply flexibility in the presence of order configuration uncertainty. We present two stochastic models: an explosion problem model and an implosion problem model. These models are positioned sequentially within a popular business process called sales and operations planning. Both models are formulated as two-stage stochastic programs with recourse and are solved using the sample average approximation method. Computational analyses were performed using data obtained from IBM System and Technology Group. The problem sets used in our analysis are created from actual industry data and our results show that significant improvements in revenue and serviceability can be achieved by appropriately accounting for the uncertainty associated with order configurations.

Original languageEnglish (US)
Pages (from-to)604-614
Number of pages11
JournalEuropean Journal of Operational Research
Volume205
Issue number3
DOIs
StatePublished - Sep 16 2010

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All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Modeling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

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