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Tuning inventory policy parameters in a small chemical company

Author

Listed:
  • R García-Flores

    (The University of Leeds)

  • X Z Wang

    (The University of Leeds)

  • T F Burgess

    (The University of Leeds)

Abstract

A project to improve inventory management in a small UK chemical company is described. A research group comprising university academics and company managers for logistics and information technology examined current practices and analysed a database of historical records of business operations of the company. Based on the analysis, a scheme to categorise stock and set ordering policies to optimise inventory costs was developed. Some comments are made on process issues and the learning that took place.

Suggested Citation

  • R García-Flores & X Z Wang & T F Burgess, 2003. "Tuning inventory policy parameters in a small chemical company," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(4), pages 350-361, April.
    • Handle: RePEc:pal:jorsoc:v:54:y:2003:i:4:d:10.1057_palgrave.jors.2601530
    DOI: 10.1057/palgrave.jors.2601530
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    References listed on IDEAS

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    1. Syntetos, A. A. & Boylan, J. E., 2001. "On the bias of intermittent demand estimates," International Journal of Production Economics, Elsevier, vol. 71(1-3), pages 457-466, May.
    2. P Keys & G Midgley, 2002. "Part Special Issue Editorial: The process of OR," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(2), pages 123-125, February.
    3. Janssen, Fred & Heuts, Ruud & de Kok, Ton, 1998. "On the (R, s, Q) inventory model when demand is modelled as a compound Bernoulli process," European Journal of Operational Research, Elsevier, vol. 104(3), pages 423-436, February.
    4. Lenard, J. D. & Roy, B., 1995. "Multi-item inventory control: A multicriteria view," European Journal of Operational Research, Elsevier, vol. 87(3), pages 685-692, December.
    5. Willemain, Thomas R. & Smart, Charles N. & Shockor, Joseph H. & DeSautels, Philip A., 1994. "Forecasting intermittent demand in manufacturing: a comparative evaluation of Croston's method," International Journal of Forecasting, Elsevier, vol. 10(4), pages 529-538, December.
    6. Altay Guvenir, H. & Erel, Erdal, 1998. "Multicriteria inventory classification using a genetic algorithm," European Journal of Operational Research, Elsevier, vol. 105(1), pages 29-37, February.
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    Cited by:

    1. Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.

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