Forschungsprojekt ::

Resilient network design with disruption uncertainty and lead times

Projektbeschreibung

On October 2018, low water levels on the river Rhine, one of Europe’s most important waterways, forced transportation to a standstill and major companies to issue profit warnings due to production losses and higher logistics cost. In increasingly complex and global supply chains, reliable transports are needed to supply products from various inbound suppliers in a cost-efficient way. However, transportation routes are prone to disruptions, such as hurricanes, low water levels or port shutdowns, resulting in transportation stops or price increases. Resilience policies, that increase the costs in steady state, aim at increasing the capability of a network to withstand, adapt and recover from disruptions. For a cost-optimal use, it is necessary to determine the optimal mix of strategic, tactical, and operational policies against the “do-nothing” scenario of risk taking under the uncertainty of disruption occurrence and impact.

We develop a decision-support model that decides on the optimal mix of resilience policies, such as multi-sourcing, inventory increase, or operational re-routing, for a two-echelon inbound supply chain with transportation disruption uncertainty to minimize total costs. The problem setting is modeled as a two-stage stochastic mixed-integer linear program (MILP).

We present a case study for the inbound supply chain design of a company with recurring transportation uncertainty on the main transportation mode. Taking disruption and lead time effects into account, a mix of resilience policies leads to cost advantages compared to the base case of risk taking. If operational re-routing as well as strategic and tactical policies are mixed, cost improvements of up to 15% can be achieved.