This paper strives for route optimization of hazardous material (hazmat) for given probabilities and consequences. We aim to not only develop a model to determine the route with the least total risk and cost, but also pursue risk equity from three perspectives of government, enterprises, and society in the route optimization. Specifically, this paper reduces the differences of population exposure risk among road segments by using the threshold setting method and decreases the differences of environmental risk by minimizing the risk compensation cost caused by the additional environmental risk exceeding its average for each road segment. In addition, this paper analyzes the impact of the time-varying characteristics of risk and risk equity and proposes a multi-objective route optimization model which considers the minimization of total risk, cost, and risk differences under time-varying conditions. Finally, the ε-constraint method and an improved genetic algorithm are used to optimize the model, which is applied to a case study involving hazardous materials transportation route optimization in Shanghai, China. The resulting analyses indicate that risk equity can be improved by setting a proper threshold to acquire feasible paths and by minimizing the compensation cost to control the differences of environmental risk. Considering variance of time in the route optimization may lead to a route with lower risk and better risk equity.
Route Optimization of Hazardous Material (Hazmat) Transportation with Risk Equity and Time-Varying Risk
Transportation Research Record: Journal of the Transportation Research Board
Transportation Research Record: Journal of the Transportation Research Board ; 2678 , 8 ; 901-918
2024-02-02
Article (Journal)
Electronic Resource
English
A Time-Varying Route Optimization Model for Urban Hazmat Transportation
British Library Conference Proceedings | 2009
|Maritime Route Risk Analysis for Hazardous Materials Transportation
British Library Conference Proceedings | 1997
|Multi-depot vehicle routing programming for hazmat transportation with weight variation risk
Taylor & Francis Verlag | 2023
|