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

Kavindra Malik and Yufei Wang

Naval Research Logistics (NRL), 1993, vol. 40, issue 7, 925-931

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.

Date: 1993
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https://doi.org/10.1002/1520-6750(199312)40:73.0.CO;2-C

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Persistent link: https://EconPapers.repec.org/RePEc:wly:navres:v:40:y:1993:i:7:p:925-931

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