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Processing Networks with Inventories: Sequential Refinement Systems

Author

Listed:
  • Yong-Joo Lee

    (Ewha Woman's University, Soeul, Korea)

  • Paul Zipkin

    (Duke University Durham, North Carolina)

Abstract

This paper investigates a model representing a make-to-stock production system, where intermediate and finished goods are produced and stored in advance of demand. In other respects the system operates much like a network of queues. There are several nodes and items. Each item is produced at one of the nodes using another item as input. Customer demands for the items and the unit-processing times at the nodes obey simple Markovian laws. We develop a tractable approximation scheme for estimating performance and test it through computer simulation. Numerical results show that the approximation is quite accurate. The model and the approximation express the effects of different degrees of component commonality.

Suggested Citation

  • Yong-Joo Lee & Paul Zipkin, 1995. "Processing Networks with Inventories: Sequential Refinement Systems," Operations Research, INFORMS, vol. 43(6), pages 1025-1036, December.
    • Handle: RePEc:inm:oropre:v:43:y:1995:i:6:p:1025-1036
    DOI: 10.1287/opre.43.6.1025
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    Citations

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    Cited by:

    1. de Kok, Ton & Grob, Christopher & Laumanns, Marco & Minner, Stefan & Rambau, Jörg & Schade, Konrad, 2018. "A typology and literature review on stochastic multi-echelon inventory models," European Journal of Operational Research, Elsevier, vol. 269(3), pages 955-983.
    2. Bo Li & Antonio Arreola‐Risa, 2021. "On minimizing downside risk in make‐to‐stock, risk‐averse firms," Naval Research Logistics (NRL), John Wiley & Sons, vol. 68(2), pages 199-213, March.
    3. Ke Fu & Vernon N. Hsu & Chung‐Yee Lee, 2011. "Approximation methods for the analysis of a multicomponent, multiproduct assemble‐to‐order system," Naval Research Logistics (NRL), John Wiley & Sons, vol. 58(7), pages 685-704, October.
    4. Sen Lin & Bo Li & Antonio Arreola-Risa & Yiwei Huang, 2023. "Optimizing a single-product production-inventory system under constant absolute risk aversion," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(3), pages 510-537, October.
    5. Bo Li & Antonio Arreola‐Risa, 2022. "Minimizing conditional value‐at‐risk under a modified basestock policy," Production and Operations Management, Production and Operations Management Society, vol. 31(4), pages 1822-1838, April.
    6. David Simchi-Levi & Yao Zhao, 2005. "Safety Stock Positioning in Supply Chains with Stochastic Lead Times," Manufacturing & Service Operations Management, INFORMS, vol. 7(4), pages 295-318, December.
    7. Liming Liu & Xiaoming Liu & David D. Yao, 2004. "Analysis and Optimization of a Multistage Inventory-Queue System," Management Science, INFORMS, vol. 50(3), pages 365-380, March.
    8. Liu, Xiaoming & Lian, Zhaotong, 2009. "Cost-effective inventory control in a value-added manufacturing system," European Journal of Operational Research, Elsevier, vol. 196(2), pages 534-543, July.
    9. van Houtum, G. J. & Inderfurth, K. & Zijm, W. H. M., 1996. "Materials coordination in stochastic multi-echelon systems," European Journal of Operational Research, Elsevier, vol. 95(1), pages 1-23, November.
    10. Avṣar, Zeynep Müge & Henk Zijm, W., 2014. "Approximate queueing models for capacitated multi-stage inventory systems under base-stock control," European Journal of Operational Research, Elsevier, vol. 236(1), pages 135-146.

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