An optimization approach to planning rail hazmat shipments in the presence of random disruptions. (October 2020)

• Record Type: Journal Article
• Authors: Jabbarzadeh, Armin; Azad, Nader; Verma, Manish
• Is Part Of: Omega. Volume 96(2020)
• Publication Date: 2020-10
• Subjects: Railroad transportation -- Hazardous materials -- Disruption management -- Bi-objective optimization -- Stochastic programming -- Risk; Management -- Periodicals; 658.4005
• DOI: 10.1016/j.omega.2019.06.004
• Languages: English
• ISSNs: 0305-0483

Abstract

Highlights: We study rail hazmat shipments in the presence of random disruptions. A bi-objective stochastic program with (expected and variability in) risk and cost objectives is developed. An augmented ε-constraint solution approach is proposed. Case study analyses suggest deploying contingency plans to mitigate hazmat risks. We demonstrate significant reduction in hazmat risk variability with minimal increase in total costs. 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.