An optimization approach to planning rail hazmat shipments in the presence of random disruptions

Abstract

Hazardous materials (hazmat) shipments are integral to the development of any industrial society, and railroad is one the primary transportation modes in North America. However, the current academic literature has not studied the impact of disruption on rail hazmat shipments. This study proposes a bi-objective two-stage stochastic program that makes use a of new measure of risk to plan rail shipments in the presence of random disruptions. Complexity of the resulting mathematical model motivated the development of an augmented ɛ-constraint solution technique, which was used to study the railroad infrastructure in Midwest United States. The resulting analyses throw light on the trade-off between hazmat risk versus cost, and suggest that deploying contingency plans for disruptions can significantly mitigate hazmat risks with only a slight increase in total cost. We also find that with less than 1% increase in the total cost, our model reduces the variability in risk by as much as 99% in our case study.