Abstract
Many key industrial and scientific processes, such as the generation of nuclear energy, are of enormous social benefit as energy demand and consumption grow over time. However, a drawback of several such processes is the production of hazardous waste materials, which often requires transportation along highway networks to treatment or disposal facilities. This waste can represent a safety hazard to civilians located along the transportation route. Most prior literature in this domain considers risk within only a single facet, and thus several important risk factors may not be considered. In our paper, we propose a multi-objective program to allow for the analysis and selection of minimally risky routes for hazardous materials transportation. The model assesses risk factors including the length of the selected route, the total population in areas surrounding the selected route, and the likelihood of an accident occurring along the selected route. Our paper uniquely uses geographic information systems (GIS) technology to model this optimization problem. This approach allows us to model risk along multiple dimensions simultaneously. We collect empirical data to test the model and present a case study for risk mitigation using a study area located in California. We show that our multi-objective approach is effective in presenting the decision-maker with a portfolio of solutions that perform well via each factor.
Highlights
Industrial and scientific processes offer enormous promise to contemporary society but often result in unusable and potentially dangerous byproducts
We argue that selecting for safer hazardous materials routes implies that companies may improve profit by Sustainability 2019, 11, 6300 materials routes implies that companies may improve profit by preventing costly delays or eventual lawsuits that may result from accidents in hazardous materials transportation; at the same time, companies may preserve their goodwill by altruistically aiming to preserve human safety
We selected nodes 3 and 145 from our dataset as start and end nodes for our hazardous material transportation problem, a user could resolve the model for any arbitrary start and end nodes
Summary
Industrial and scientific processes offer enormous promise to contemporary society but often result in unusable and potentially dangerous byproducts These substances, often dubbed hazardous materials, present enormous logistical challenges for organizations that need to dispose of them without subjecting human populations and the environment to undue risk [1,2,3]. Local, state, and federal laws dictate that highway routing schemes for transportation of hazardous materials must be designed to preserve human safety. These laws generally serve two purposes: first, to ban transportation of hazardous materials along specific road segments, and second, to establish legal liability of the transporter in the event of an accident. In the United States, the Hazardous Materials Transportation Act (HMTA), enacted in 1975, is the most widely known such law on a federal level [8]
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