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An integrated guaranteed- and stochastic-service approach to inventory optimization in supply chains


  • Klosterhalfen, Steffen T.
  • Dittmar, Daniel
  • Minner, Stefan


Multi-echelon inventory optimization literature distinguishes stochastic- (SS) and guaranteed-service (GS) approaches as mutually exclusive frameworks. While the GS approach considers flexibility measures at the stages to deal with stockouts, the SS approach only relies on safety stock. Within a supply chain, flexibility levels might differ between stages rendering them appropriate candidates for one approach or the other. The existing approaches, however, require the selection of a single framework for the entire supply chain instead of a stage-wise choice. We develop an integrated hybrid-service (HS) approach which endogenously determines the overall cost-optimal approach for each stage and computes the required inventory levels. We present a dynamic programming optimization algorithm for serial supply chains that partitions the entire system into subchains of different types. From a numerical study we find that, besides implicitly choosing the better of the two pure frameworks, whose cost differences can be considerable, the HS approach enables additional pipeline and on-hand stock cost savings. We further identify drivers for the preferability of the HS approach.

Suggested Citation

  • Klosterhalfen, Steffen T. & Dittmar, Daniel & Minner, Stefan, 2013. "An integrated guaranteed- and stochastic-service approach to inventory optimization in supply chains," European Journal of Operational Research, Elsevier, vol. 231(1), pages 109-119.
  • Handle: RePEc:eee:ejores:v:231:y:2013:i:1:p:109-119
    DOI: 10.1016/j.ejor.2013.05.032

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    References listed on IDEAS

    1. Stephen C. Graves & Sean P. Willems, 2000. "Optimizing Strategic Safety Stock Placement in Supply Chains," Manufacturing & Service Operations Management, INFORMS, vol. 2(1), pages 68-83, June.
    2. Andrew J. Clark & Herbert Scarf, 2004. "Optimal Policies for a Multi-Echelon Inventory Problem," Management Science, INFORMS, vol. 50(12_supple), pages 1782-1790, December.
    3. Stephen C. Graves & Sean P. Willems, 2005. "Optimizing the Supply Chain Configuration for New Products," Management Science, INFORMS, vol. 51(8), pages 1165-1180, August.
    4. Eric Logan Huggins & Tava Lennon Olsen, 2003. "Supply Chain Management with Guaranteed Delivery," Management Science, INFORMS, vol. 49(9), pages 1154-1167, September.
    5. 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.
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    Cited by:

    1. repec:eee:ejores:v:269:y:2018:i:3:p:955-983 is not listed on IDEAS
    2. repec:eee:proeco:v:197:y:2018:i:c:p:330-341 is not listed on IDEAS
    3. repec:spr:annopr:v:242:y:2016:i:2:d:10.1007_s10479-014-1635-1 is not listed on IDEAS
    4. Wang, Yulan & Wallace, Stein W. & Shen, Bin & Choi, Tsan-Ming, 2015. "Service supply chain management: A review of operational models," European Journal of Operational Research, Elsevier, vol. 247(3), pages 685-698.
    5. Eruguz, Ayse Sena & Sahin, Evren & Jemai, Zied & Dallery, Yves, 2016. "A comprehensive survey of guaranteed-service models for multi-echelon inventory optimization," International Journal of Production Economics, Elsevier, vol. 172(C), pages 110-125.


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