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Integrating supplier selection with inventory management under supply disruptions

Author

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  • Thomy Eko Saputro
  • Gonçalo Figueira
  • Bernardo Almada-Lobo

Abstract

In the current global market, managing supply is not a straightforward process and it becomes even more complex as uncertainty and disruptions occur. In order to mitigate their impact, the selection of suppliers of strategic items should have a more holistic view of the operations in the supply chain. We propose an integrated model for supplier selection, considering inventory management and inbound transportation. We approach this problem, incorporating stochastic demand and suppliers' imperfect quality. Imperfect quality triggers additional costs, including external failure and holding costs. Supply disruptions also affect the suppliers' lead time, resulting in delivery delays. We develop a methodology to address this challenge with simulation-optimisation. A genetic algorithm determines supplier selection decisions, while inventory decisions are computed analytically. Discrete-event simulation is used to evaluate the overall performance, as well as to update the lead time dynamically, according to the disruptions. Finally, sensitivity analysis providing managerial insights reveals that criteria in supplier selection should be given a different priority depending on the characteristics of the items, and the effectiveness of disruption mitigation strategies depends on the disruption characteristics.

Suggested Citation

  • Thomy Eko Saputro & Gonçalo Figueira & Bernardo Almada-Lobo, 2021. "Integrating supplier selection with inventory management under supply disruptions," International Journal of Production Research, Taylor & Francis Journals, vol. 59(11), pages 3304-3322, June.
  • Handle: RePEc:taf:tprsxx:v:59:y:2021:i:11:p:3304-3322
    DOI: 10.1080/00207543.2020.1866223
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    Cited by:

    1. Carlos Cuartas & Jose Aguilar, 2023. "Hybrid algorithm based on reinforcement learning for smart inventory management," Journal of Intelligent Manufacturing, Springer, vol. 34(1), pages 123-149, January.
    2. 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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