A Mathematical Modeling approach for Supply Chain Management under
Disruption and Operational Uncertainty
Abstract
In this work, we proposed a two-stage stochastic programming model for a
four-echelon supply chain problem considering possible disruptions at
the nodes (supplier and facilities) as well as the connecting
transportation modes and operational uncertainties in form of uncertain
demands. The first stage decisions are supplier choice, capacity levels
for manufacturing sites and warehouses, inventory levels, transportation
modes selection, and shipment decisions for the certain periods, and the
second stage anticipates the cost of meeting future demands subject to
the first stage decision. Comparing the solution obtained for the
two-stage stochastic model with a multi-period deterministic model shows
that the stochastic model makes a better first stage decision to hedge
against the future demand. This study demonstrates the managerial
viability of the proposed model in decision making for supply chain
network in which both disruption and operational uncertainties are
accounted for.