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Efficient computation of time-based customer service levels in a multi-item, multi-echelon supply chain: A practical approach for inventory optimization

Author

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  • Caggiano, Kathryn E.
  • Jackson, Peter L.
  • Muckstadt, John A.
  • Rappold, James A.

Abstract

Time-based item fill rates, or "channel" fill rates, are the building blocks needed to evaluate steady-state compliance with time-based customer service agreements. Exact computation of channel fill rates is both difficult and time-consuming, yet their accurate assessment is essential for system-wide inventory optimization. We describe and validate a practical method for computing channel fill rates in a multi-item, multi-echelon service parts distribution system. A simulation study is presented which shows that, in a three-echelon setting, our estimation errors are very small over a wide range of base stock level vectors. A more accurate, though less efficient, approximation method is also evaluated for comparison.

Suggested Citation

  • Caggiano, Kathryn E. & Jackson, Peter L. & Muckstadt, John A. & Rappold, James A., 2009. "Efficient computation of time-based customer service levels in a multi-item, multi-echelon supply chain: A practical approach for inventory optimization," European Journal of Operational Research, Elsevier, vol. 199(3), pages 744-749, December.
    • Handle: RePEc:eee:ejores:v:199:y:2009:i:3:p:744-749
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    References listed on IDEAS

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    1. Stephen C. Graves, 1985. "A Multi-Echelon Inventory Model for a Repairable Item with One-for-One Replenishment," Management Science, INFORMS, vol. 31(10), pages 1247-1256, October.
    2. Markus Ettl & Gerald E. Feigin & Grace Y. Lin & David D. Yao, 2000. "A Supply Network Model with Base-Stock Control and Service Requirements," Operations Research, INFORMS, vol. 48(2), pages 216-232, April.
    3. Kathryn E. Caggiano & Peter L. Jackson & John A. Muckstadt & James A. Rappold, 2007. "Optimizing Service Parts Inventory in a Multiechelon, Multi-Item Supply Chain with Time-Based Customer Service-Level Agreements," Operations Research, INFORMS, vol. 55(2), pages 303-318, April.
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    1. van Wijk, A.C.C. & Adan, I.J.B.F. & van Houtum, G.J., 2012. "Approximate evaluation of multi-location inventory models with lateral transshipments and hold back levels," European Journal of Operational Research, Elsevier, vol. 218(3), pages 624-635.
    2. Noordhoek, Marije & Dullaert, Wout & Lai, David S.W. & de Leeuw, Sander, 2018. "A simulation–optimization approach for a service-constrained multi-echelon distribution network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 292-311.
    3. Patriarca, Riccardo & Costantino, Francesco & Di Gravio, Giulio & Tronci, Massimo, 2016. "Inventory optimization for a customer airline in a Performance Based Contract," Journal of Air Transport Management, Elsevier, vol. 57(C), pages 206-216.
    4. Sahba, Pedram & BalcIog[small tilde]lu, BarIs, 2011. "The impact of transportation delays on repairshop capacity pooling and spare part inventories," European Journal of Operational Research, Elsevier, vol. 214(3), pages 674-682, November.
    5. Jeet, Vishv & Kutanoglu, Erhan, 2018. "Part commonality effects on integrated network design and inventory models for low-demand service parts logistics systems," International Journal of Production Economics, Elsevier, vol. 206(C), pages 46-58.
    6. Pal, Brojeswar & Sana, Shib Sankar & Chaudhuri, Kripasindhu, 2012. "A three layer multi-item production–inventory model for multiple suppliers and retailers," Economic Modelling, Elsevier, vol. 29(6), pages 2704-2710.
    7. Dreyfuss, Michael & Giat, Yahel, 2017. "Optimal spares allocation to an exchangeable-item repair system with tolerable wait," European Journal of Operational Research, Elsevier, vol. 261(2), pages 584-594.
    8. Yahel Giat, 2024. "Stock Levels and Repair Sourcing in a Periodic Review Exchangeable Item Repair System," Logistics, MDPI, vol. 8(2), pages 1-19, March.
    9. Araceli Zavala & David Nowicki & Jose Emmanuel Ramirez-Marquez, 2019. "Quantitative metrics to analyze supply chain resilience and associated costs," Journal of Risk and Reliability, , vol. 233(2), pages 186-199, April.
    10. Tsai, Shing Chih & Zheng, Ya-Xin, 2013. "A simulation optimization approach for a two-echelon inventory system with service level constraints," European Journal of Operational Research, Elsevier, vol. 229(2), pages 364-374.
    11. Nowicki, David R. & Randall, Wesley S. & Ramirez-Marquez, Jose Emmanuel, 2012. "Improving the computational efficiency of metric-based spares algorithms," European Journal of Operational Research, Elsevier, vol. 219(2), pages 324-334.
    12. Selçuk, B., 2013. "An adaptive base stock policy for repairable item inventory control," International Journal of Production Economics, Elsevier, vol. 143(2), pages 304-315.
    13. Dreyfuss, Michael & Giat, Yahel, 2019. "Allocating spares to maximize the window fill rate in a periodic review inventory system," International Journal of Production Economics, Elsevier, vol. 214(C), pages 151-162.

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