Risk Management for a Global Supply Chain Planning Under Uncertainty: Models and Algorithms
Source: Carnegie Mellon University
This paper considers the risk management for mid-term planning of a global multi-product chemical supply chain under demand and freight rate uncertainty. A two-stage linear stochastic programming approach is proposed within a multi-period planning model that takes into account the production and inventory levels, transportation modes, times of shipments and customer service levels. To investigate the potential improvement by using stochastic programming, the authors describe a simulation framework that relies on a rolling horizon approach.