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An improved algorithm for the dynamic lot‐sizing problem with learning effect in setups

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  • Kavindra Malik
  • Yufei Wang

Abstract

The dynamic lot‐sizing problem with learning in setups is a variation of the Wagner‐Whitin lot‐sizing problem where the setup costs are a concave, nondecreasing function of the cumulative number of setups. This problem has been a subject of some recent research. We extend the previously studied model to include nonstationary production costs and present an O(T2) algorithm to solve this problem. The worst‐case complexity of our algorithm improves the worst‐case behavior of the algorithms presently known in the literature. © 1993 John Wiley & Sons, Inc.

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  • Kavindra Malik & Yufei Wang, 1993. "An improved algorithm for the dynamic lot‐sizing problem with learning effect in setups," Naval Research Logistics (NRL), John Wiley & Sons, vol. 40(7), pages 925-931, December.
    • Handle: RePEc:wly:navres:v:40:y:1993:i:7:p:925-931
    DOI: 10.1002/1520-6750(199312)40:73.0.CO;2-C
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    1. Willard I. Zangwill, 1968. "Minimum Concave Cost Flows in Certain Networks," Management Science, INFORMS, vol. 14(7), pages 429-450, March.
    2. Chand, Suresh, 1989. "Lot sizes and setup frequency with learning in setups and process quality," European Journal of Operational Research, Elsevier, vol. 42(2), pages 190-202, September.
    3. Suresh Chand & Suresh P. Sethi, 1990. "A Dynamic Lot Sizing Model with Learning in Setups," Operations Research, INFORMS, vol. 38(4), pages 644-655, August.
    4. Kirk R. Karwan & Joseph B. Mazzola & Richard C. Morey, 1988. "Production lot sizing under setup and worker learning," Naval Research Logistics (NRL), John Wiley & Sons, vol. 35(2), pages 159-175, April.
    5. Awi Federgruen & Michal Tzur, 1991. "A Simple Forward Algorithm to Solve General Dynamic Lot Sizing Models with n Periods in 0(n log n) or 0(n) Time," Management Science, INFORMS, vol. 37(8), pages 909-925, August.
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