Catastrophe avoidance models for hazardous materials route planning

The most-widely used definition of risk in the hazardous materials transportation literature is the expected consequence of an incident (accident resulting in a release), which, for each edge of the network, is equal to the product of the incident probability and a quantifiable consequence (such as number of people evacuated). This definition ignores the risk-averse attitudes of many decision-makers when dealing with low, probability/high consequence events. We suggest that avoiding a catastrophe tan incident with a very large consequence) may be a relevant issue in routing hazardous materials, and we introduce three different catastrophe-avoidance models. In the first model, catastrophe avoidance is achieved by minimizing the maximum population exposure. In the second model, the variance of the route consequence is incorporated into the decision. In the third model, an explicit disutility function is used. We show that all three models reduce to a standard shortest path problem. Each model avoids high-population areas of the transport network. We give numerical examples and discuss the similarities and the differences among the three models. The first of the three models suggested may be the most intuitive, and is the most tractable computationally. implementation of the other two models may be difficult due to scaling issues. Nevertheless, these models offer theoretical insight that may be valuable to researchers.