A stochastic program to evaluate disruption mitigation investments in the supply chain

André Snoeck*, Maximiliano Udenio, Jan C. Fransoo

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Supply chain risk management is becoming increasingly important due to a variety of natural and man-made uncertainties. We develop a methodology to evaluate the costs of disruptions and the value of supply chain network mitigation options based on a two-stage stochastic program. To solve the model, we rely on a solution scheme based on sample average approximation. We explicitly differentiate between disruption periods and business as usual periods to decrease the model size and computational requirements by approximately 85% and 95%, respectively. Furthermore, the decrease in model complexity allows us to include the conditional value at risk in the objective function to incorporate the risk aversion of decisions makers. Based on a case study of a chemical supply chain, this study shows the trade-off between long-term expected costs minimization and short term risk minimization, where the latter leads to a more aggressive investment policy.
Original languageEnglish
Pages (from-to)516-530
Number of pages15
JournalEuropean Journal of Operational Research
Volume274
Issue number2
DOIs
Publication statusPublished - 16 Apr 2019
Externally publishedYes

Keywords

  • Stochastic programming
  • Supply chain network design
  • Supply chain risk management

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