TY - JOUR
T1 - Sustainable risk mitigation in hazardous material transportation
AU - De Maio, Annarita
AU - Laporte, Gilbert
AU - Musmanno, Roberto
AU - Vocaturo, Francesca
PY - 2025/8/6
Y1 - 2025/8/6
N2 - The transportation of hazardous material involves the movement of freight representing a high risk to health, safety, and the environment. Due to its nature, hazardous material transportation is regulated by strict laws and must be treated separately from classical transportation. This study addresses road transportation of hazardous materials as a variant of the hazmat vehicle routing and scheduling problem with time windows. The model incorporates a multi-criteria risk measure, balancing factors such as accident probability, population density, distance from fire stations, and traffic conditions, while considering time-dependent travel times divided into distinct time zones. The problem is formulated as a three-objective optimization model to minimize total risk, arrival time, and vehicle cost. A late acceptance hill-climbing heuristic is introduced to obtain feasible solutions. Computational experiments on test instances demonstrate the heuristic’s efficiency and ability to generate high-quality solutions in reduced execution times. Subsequently, the heuristic is applied to a case study on a Northern Italy road network involving the transportation of compressed oxygen by a logistics operator, providing actionable managerial insights.
AB - The transportation of hazardous material involves the movement of freight representing a high risk to health, safety, and the environment. Due to its nature, hazardous material transportation is regulated by strict laws and must be treated separately from classical transportation. This study addresses road transportation of hazardous materials as a variant of the hazmat vehicle routing and scheduling problem with time windows. The model incorporates a multi-criteria risk measure, balancing factors such as accident probability, population density, distance from fire stations, and traffic conditions, while considering time-dependent travel times divided into distinct time zones. The problem is formulated as a three-objective optimization model to minimize total risk, arrival time, and vehicle cost. A late acceptance hill-climbing heuristic is introduced to obtain feasible solutions. Computational experiments on test instances demonstrate the heuristic’s efficiency and ability to generate high-quality solutions in reduced execution times. Subsequently, the heuristic is applied to a case study on a Northern Italy road network involving the transportation of compressed oxygen by a logistics operator, providing actionable managerial insights.
UR - https://www.scopus.com/pages/publications/105012983701
U2 - 10.1016/j.cor.2025.107228
DO - 10.1016/j.cor.2025.107228
M3 - Article
SN - 0305-0548
VL - 184
JO - Computers and Operations Research
JF - Computers and Operations Research
M1 - 107228
ER -