Li Tan and Shenghan Xu. In Proceedings of the 2010 annual meeting of Production and Operation Management Society. Vancouver, Cananda. May, 2010.

The policy of pooling lead-time risk by simultaneously splitting replenishment orders among several suppliers continues to attract the attention of researchers and industrial practitioners in past two decades. Nevertheless, traditional risk analysis approaches used in studying order splitting policy have their limitation on scalability (e.g. stochastic modeling and proving) and/or accuracy (e.g. statistic experiments). To address these shortcomings, in this paper we propose a probabilistic-model-checking-based approach to study the impact of different factors of order splitting policy on risk reduction. We model stochastic behaviors of supply chains using an extension of Markov Decision Processes and translate the goal of risk analysis into a temporal logic. We then use probabilistic model checking to analyze different risk factors in a stochastic supply chain model with order splitting policy, and to identify some key factors that can help reduce lead-time risk.