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Algorithms and heuristics for variable‐yield lot sizing

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  • Joseph B. Mazzola
  • William F. McCoy
  • Harvey M. Wagner

Abstract

We consider the multiperiod lot‐sizing problem in which the production yield (the proportion of usable goods) is variable according to a known probability distribution. We review two economic order quantity (EOQ) models for the stationary demand continuous‐time problem and derive an EOQ model when the production yield follows a binomial distribution and backlogging of demand is permitted. A dynamic programming algorithm for an arbitrary sequence of demand requirements is presented. Heuristics based on both the EOQ model and appropriate modification of the underlying perfect‐yield lot‐sizing policies are discussed, and extensive computational evaluation of these heuristics is presented. Two of these heuristics are then modified to include the notion of supply safety stock. The modified heuristics consistently produce near‐optimal lot‐sizing policies for problems with stationary and time‐varying demands.

Suggested Citation

  • Joseph B. Mazzola & William F. McCoy & Harvey M. Wagner, 1987. "Algorithms and heuristics for variable‐yield lot sizing," Naval Research Logistics (NRL), John Wiley & Sons, vol. 34(1), pages 67-86, February.
    • Handle: RePEc:wly:navres:v:34:y:1987:i:1:p:67-86
    DOI: 10.1002/1520-6750(198702)34:13.0.CO;2-R
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    References listed on IDEAS

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    Cited by:

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    4. Gel, Esma S. & Salman, F. Sibel, 2022. "Dynamic ordering decisions with approximate learning of supply yield uncertainty," International Journal of Production Economics, Elsevier, vol. 243(C).

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