In the article authored by Daniel Müllerklein and Pirmin Fontaine, we developed a decision-support model to minimize total costs for supply chains facing uncertainties due to transportation disruptions by determining the optimal combination of resilience strategies such as multi-sourcing, inventory, or operational re-routing. The problem is modeled as a two-stage stochastic mixed-integer linear program that explicitly considers lead times. To solve large instances, a Benders decomposition approach is proposed, enhanced with lower-bound lifting, valid inequalities, branch-and-benders-cut, and a warm-start heuristic. In the numerical study, we show that a mix of resilience strategies across strategic, tactical, and operational levels can lead to cost improvements of up to 50%. Additionally, we demonstrate that predictable disruptions can reduce resilience costs by a further 10% if sufficient re-routing capacities are available.
The article is now available online here