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.
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