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Effects of Learning on Optimal Lot Size

Author

Listed:
  • E. C. Keachie

    (Associate Professor of Industrial Engineering, University of California)

  • Robert J. Fontana

    (Associate Professor of Industrial Engineering, University of California)

Abstract

This paper deals with the effects of learning on the calculation of optimal economic lot sizes in intermittent production. It is assumed that the manufacturing time of the lots is of such length that phenomena usually called "learning" can be encountered within each lot. The three different cases that can occur are incorporated into a model which demonstrates that the traditional lot size formulae may well indicate lots that are smaller than the true optimum. Numerical examples show the significance of these differences. A simple deterministic model is used but results are seen to be extended easily to more complex cases.

Suggested Citation

  • E. C. Keachie & Robert J. Fontana, 1966. "Effects of Learning on Optimal Lot Size," Management Science, INFORMS, vol. 13(2), pages 102-108, October.
  • Handle: RePEc:inm:ormnsc:v:13:y:1966:i:2:p:b102-b108
    DOI: 10.1287/mnsc.13.2.B102
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    Citations

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    Cited by:

    1. B. C. Giri & M. Masanta, 2022. "A closed-loop supply chain model with uncertain return and learning-forgetting effect in production under consignment stock policy," Operational Research, Springer, vol. 22(2), pages 947-975, April.
    2. Yang, Wen-Hua & Chand, Suresh, 2008. "Learning and forgetting effects on a group scheduling problem," European Journal of Operational Research, Elsevier, vol. 187(3), pages 1033-1044, June.
    3. Chiu, Huan Neng & Chen, Hsin Min, 2005. "An optimal algorithm for solving the dynamic lot-sizing model with learning and forgetting in setups and production," International Journal of Production Economics, Elsevier, vol. 95(2), pages 179-193, February.
    4. Chen, Cheng-Kang & Lo, Chih-Chung & Liao, Yi-Xiang, 2008. "Optimal lot size with learning consideration on an imperfect production system with allowable shortages," International Journal of Production Economics, Elsevier, vol. 113(1), pages 459-469, May.
    5. Biskup, Dirk, 2008. "A state-of-the-art review on scheduling with learning effects," European Journal of Operational Research, Elsevier, vol. 188(2), pages 315-329, July.
    6. Jaber, Mohamad Y. & El Saadany, Ahmed M.A., 2011. "An economic production and remanufacturing model with learning effects," International Journal of Production Economics, Elsevier, vol. 131(1), pages 115-127, May.
    7. Amrina Kausar & Ahmad Hasan & Chandra K. Jaggi, 2023. "Sustainable inventory management for a closed-loop supply chain with learning effect and carbon emission under the multi-shipment policy," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(5), pages 1738-1755, October.
    8. Pritibhushan Sinha, 2021. "Some results on an assignment problem variant," OPSEARCH, Springer;Operational Research Society of India, vol. 58(1), pages 144-147, March.
    9. Mazzola, Joseph B. & Neebe, Alan W. & Rump, Christopher M., 1998. "Multiproduct production planning in the presence of work-force learning," European Journal of Operational Research, Elsevier, vol. 106(2-3), pages 336-356, April.
    10. Hwang, Juhwen & Wan, Yat-wah, 2013. "A supplier–retailer supply chain with intermediate storage for batch ordering," International Journal of Production Economics, Elsevier, vol. 142(2), pages 343-352.
    11. Ogawa, Sanae & Ohta, Hiroshi, 1995. "Common order cycle system for multi-item inventory model with learning in ordering and transportation," International Journal of Production Economics, Elsevier, vol. 41(1-3), pages 321-325, October.
    12. Jaber, Mohamad Y. & Bonney, Maurice, 2007. "Economic manufacture quantity (EMQ) model with lot-size dependent learning and forgetting rates," International Journal of Production Economics, Elsevier, vol. 108(1-2), pages 359-367, July.

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