Abstract
Hazardous materials transportation involves extensive risk and cannot be avoided in practice. An advanced routing, however, can help to reduce the risk by planning the best transportation routes for hazardous materials that can make effective tradeoffs between the risk objective and the economic objective. In this study, we explore the hazardous materials routing problem in the road-rail multimodal transportation network with a hub-and-spoke structure, in which the risk is measured by the multiplication of population exposure and the associated volume of hazardous materials, and minimizing the total risk of all the transportation orders of hazardous materials is set as the risk objective. It is difficult to estimate the population exposure exactly during the routing decision-making process, which results in its uncertainty. In this study, we formulate the uncertain population exposure from a fuzzy programming perspective by using triangular fuzzy numbers. Moreover, the carbon dioxide emission constraint is formulated to realize the sustainable transportation of hazardous materials. To optimize the problem under the above framework, we first establish a bi-objective fuzzy mixed integer nonlinear programming model, and then develop a three-stage exact solution strategy that the combines fuzzy credibilistic chance constraint, linearization technique, and the normalized weighting method. Finally, a computational experiment is carried out to verify the feasibility of the proposed method in dealing with the problem. The experimental results indicate that tradeoffs between the two conflicting objectives can be effectively made by using the Pareto frontier to the hazardous materials routing problem. Furthermore, the credibility level and carbon dioxide emission cap significantly influence the hazardous materials routing optimization. Their effects on the optimization result are quantified by using sensitivity analysis, which can draw some useful insights to help decision makers to better organize the hazardous materials road-rail multimodal transportation under uncertainty and sustainability.
Highlights
We systematically investigate the hazardous materials road‐rail multimodal routing problem that is a spotlight in the transportation planning field
The following three extensions are made in order to improve the problem optimization: (1) A hub-and-spoke network is used to represent the hazardous materials road-rail multimodal transportation network; (2) the uncertainty of the risk parameter, i.e., the population exposures, is considered
As for solving the specific problem formulated by a bi-objective fuzzy mixed integer nonlinear programming model, we develop a three-stage exact solution strategy that combines fuzzy credibilistic chance constraint, linearization technique, and the normalized weighing method
Summary
Background Hazardous materials transportation plays an important role in the transportation industry and has been given remarkable importance over the last decades [1]. The hazardous materials transportation is associated with tremendous risk that can cause human life and economic losses [5]. China suffers a lot from transportation accidents involving hazardous materials [9]. The question of how to effectively manage the hazardous materials transportation to reduce risk has drawn great attention from government, transportation providers and demanders as well as transportation planners. The U.S Hazardous Materials Transportation Uniform Safety Act of 1993 strongly acknowledged the route decision-making as an effective way to reduce risk from hazardous materials transportation [10]. The hazardous materials routing problem has become one of the spotlights in the transportation planning field [11]
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