Dynamic Models for Supply Chain Planning in Oilfield Services Industry: A Case for Hybrid Cross-Docks

Abstract

We consider a supply chain planning problem via efficient cross-docking for oilfield services industry. The problem is motivated from a major oilfield services company in North America. In a typical supply chain setup of this industry, the companies ship raw materials to an international location (typically a Free Trade Zone), which serves as the stock consolidation point for the region, break-bulk and then ship to field locations (oil excavation sites also called plants). In this research, the consolidation points are hybrid cross-docks (HCD), where raw materials can be stored free of cost for a specific period of time. The supply chain problem involves minimizing the total inbound and outbound transportation costs and the inventory management costs at the cross-docking facility and the plants. In this context, we analyze two problems under the following scenarios: (i) all raw-materials required at each plant (outbound delivery) are shipped periodically by the company from the HCD, and (ii) the outbound delivery is outsourced to a 3PL. For the first problem, we perform complexity analysis, use discrete optimization, and develop a heuristic algorithm. For the second problem, we perform stochastic analysis and robust optimization. The first scenario gives rise to new integrated inventory and logistics models. The second scenario provides new theoretical models and analysis for a variation of the dynamic lot-sizing problem. This paper demonstrates the use of a modeling approach that not only meets this need for this specific industry, but also has the potential to be applied to other industries with similar supply chain structure.