Supply chain planning with free trade zone and uncertain demand

Our research is inspired by the subcontracting problem at a major oil field services company in North America. The company’s supply chain consists of suppliers bringing raw materials to a Free Trade Zone (FTZ). The FTZ receives raw materials in full containers from various suppliers, and then the company ships them to various plants (e.g. oil excavation sites) frequently via subcontractors. This allows the company to focus on managing only the inbound transportation and inventory at the FTZ. The demand for each raw material is stochastic. We derive an algorithm running at polynomial time for the stochastic programming formulation and perform $\mu -$ regret Robust Optimization to handle the demand uncertainty. We also use a Sample Average Approximation method to alleviate the high computational requirement of the robust optimization model. The modeling approach demonstrated by this paper not only meets the needs of this specific company and industry but also can be applied to other industries with similar supply chain structures.