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Exploring the Potential Use of the Birnbaum-Saunders Distribution in Inventory Management

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  • Peter Wanke
  • Víctor Leiva

Abstract

Choosing the suitable demand distribution during lead-time is an important issue in inventory models. Much research has explored the advantage of following a distributional assumption different from the normality. The Birnbaum-Saunders (BS) distribution is a probabilistic model that has its genesis in engineering but is also being widely applied to other fields including business, industry, and management. We conduct numeric experiments using the R statistical software to assess the adequacy of the BS distribution against the normal and gamma distributions in light of the traditional lot size-reorder point inventory model, known as ( , ). The BS distribution is well-known to be robust to extreme values; indeed, results indicate that it is a more adequate assumption under higher values of the lead-time demand coefficient of variation, thus outperforming the gamma and the normal assumptions.

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  • Peter Wanke & Víctor Leiva, 2015. "Exploring the Potential Use of the Birnbaum-Saunders Distribution in Inventory Management," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-9, October.
    • Handle: RePEc:hin:jnlmpe:827246
    DOI: 10.1155/2015/827246
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    Cited by:

    1. Fernando Rojas & Peter Wanke & Víctor Leiva & Mauricio Huerta & Carlos Martin-Barreiro, 2022. "Modeling Inventory Cost Savings and Supply Chain Success Factors: A Hybrid Robust Compromise Multi-Criteria Approach," Mathematics, MDPI, vol. 10(16), pages 1-18, August.

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