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A Two-Stage Stochastic Model for Distribution Logistics with Transshipment and Backordering: Stochastic Versus Deterministic Solutions

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New Trends in Emerging Complex Real Life Problems

Part of the book series: AIRO Springer Series ((AIROSS,volume 1))

Abstract

We present a two-stage stochastic program for a distribution logistic system with transshipment and backordering under stochastic demand and we first argue that it is NP-hard. Then, we perform a computational analysis based on a distribution network. In the case with two retailers, we show that modeling uncertainty with a stochastic program leads to better solutions with respect to the ones provided by the deterministic program, especially if limited recourse actions are admitted. Although there are special cases in which the deterministic and the stochastic solutions select the same retailers towards which sending items, in general, the deterministic solution cannot be upgraded in order to find the optimal solution of the stochastic program. Finally, in the case with four retailers, transshipment can provide more flexibility and better results.

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Authors and Affiliations

  1. University of Bergamo, Via dei Caniana, 2, Bergamo, Italy

    Rossana Cavagnini & Francesca Maggioni

  2. University of Brescia, Contrada Santa Chiara, 50, Brescia, Italy

    Luca Bertazzi

Authors
  1. Rossana Cavagnini
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  2. Luca Bertazzi
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  3. Francesca Maggioni
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Corresponding author

Correspondence to Rossana Cavagnini .

Editor information

Editors and Affiliations

  1. Department of Mathematics and Computer Science, University of Catania, Catania, Italy

    Patrizia Daniele

  2. Department of Mathematics and Computer Science, University of Catania, Catania, Italy

    Laura Scrimali

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Cavagnini, R., Bertazzi, L., Maggioni, F. (2018). A Two-Stage Stochastic Model for Distribution Logistics with Transshipment and Backordering: Stochastic Versus Deterministic Solutions. In: Daniele, P., Scrimali, L. (eds) New Trends in Emerging Complex Real Life Problems. AIRO Springer Series, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-030-00473-6_15

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