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Journal Article

Citation

Lai YC, Kawprasert A, Lin CY, Saat MR, Liang CH, Barkan CPL. Transp. Res. Rec. 2011; 2261: 115-123.

Copyright

(Copyright © 2011, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.3141/2261-13

PMID

unavailable

Abstract

Rail transport plays a key role in safely and economically moving hazardous materials from production to consumption points. As a result of heightened safety and security concerns, interest in all possible means of reducing the risk of transporting hazardous materials has intensified in recent years. Various approaches to railroad accident prevention--including infrastructure improvements, packaging enhancements, operational changes, and alteration of the route structure--are available. Operations research techniques have been applied to consider each approach individually, but no technique has integrated the approaches into a single model. This study introduced an integrated mathematical model to formally consider a combination of approaches to reduce risk. The framework enabled simultaneous consideration of route choices, tank car safety designs, and track maintenance to determine an optimal strategy that minimized risk and costs. Model formulation was provided in the form of nonlinear and mixed-integer programming. For illustration, a small-scale, hypothetical network flow of a hazardous material was considered. Numerical results showed that the optimal strategy could substantially reduce risk with a marginal increase in costs. The integrated model provided a framework for choosing the most effective risk-mitigation strategy for a particular rail network given various constraints. It could be applied to multiple types of commodities and adapted to address various questions for local, regional, or systemwide planning and decision making to provide the safest transportation possible given constrained resources. The framework would be particularly beneficial to rail carriers interested in how to best allocate safety and engineering resources to maximize safety.

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