Selection of a dynamic supply portfolio under delay and disruption risks

The problem of a multi-period supplier selection and order quantity allocation in the presence of supply chain disruption and delay risks is considered. Given a set of customer orders for finished products, the decision-maker needs to decide from which supplier and when to deliver product-specific parts required for each customer order to meet customer requested due date at a low cost or a high service level and to mitigate the impact of supply chain risks. For the selection of risk-neutral or risk-averse dynamic supply portfolio, a scenario-based stochastic mixed integer programming approach is developed. In the scenario analysis, the low probability and high impact supply disruptions are combined with the high probability and low impact supply delays. The risk-neutral portfolio is optimised by minimising expected cost or maximising expected service level. The risk-averse portfolio is optimised by calculating cost- or service-at-risk and minimising conditional cost-at risk or maximising conditional service at risk. The proposed dynamic portfolio approach leads to a time-indexed stochastic MIP formulation with a strong LP relaxation, which has proven to be computationally very efficient. The findings indicate that neglecting potential delay risks in supplier selection may lead to greater supply fluctuations and manufacturing delays.