Cost efficient robust global supply chain system design under uncertainty

Abstract

Brutal competitions in today’s global supply chain have forced business enterprises to focus attention on their supply chains. These issues have guided this research to introduce a supply chain service level measure and develop a novel robust design optimization (RDO) approach to assure service level rate requirements and minimize total service level costs. A supply chain system design must maintain its efficiency over time while coping with the uncertainty in production and transportation. Unexpected delay in the product flow can render the supply chain system inefficient with respect to service level costs. Analytical models for the determination of the risk involved in a supply chain system design are difficult to derive when uncertainty is involved in the supply chain. In this paper, the service level rate measure approach is detailed first. Then, the methodology for the robust design optimization-based approach is provided. Two case studies are performed to demonstrate the effectiveness of the proposed service level measure and developed robust design optimization model. Results from the two case studies have shown that by implementing the developed robust design optimization approach, a system is able to achieve a 90 % service level rate while minimizing performance cost and uncertainty impact.