TY - CHAP
T1 - Dynamic Routing Algorithm for Hazmat Transportation Problems
AU - Hu, Ta Yin
AU - Hsu, Yu Cheng
AU - Liao, Tsai Yun
N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This paper is based on work supported by the Ministry of Science and Technology (Project: 105-2410-H-006-060), Taiwan, R.O.C.
Publisher Copyright:
© National Academy of Sciences: Transportation Research Board 2022.
PY - 2022/11
Y1 - 2022/11
N2 - After a series of gas pipeline explosions in Kaohsiung City, Taiwan, in 2014, the Environmental Protection Administration (EPA) issued regulations in 2017 requiring all chemical tank trucks to be equipped with GPS for real-time monitoring and control. Hazmat transportation problems, along with solution algorithms and applications, have been studied extensively. However, most of the research has focused on the route planning level. Dynamic characteristics should be incorporated to reflect possible dynamic traffic situations with more advanced information and communication capabilities for chemical tank trucks. This research formulates a bi-objective dynamic model and proposes a solution algorithm based on a genetic algorithm (GA) for dynamic hazmat route optimization. A dynamic bi-objective model, including transportation cost and risk, is developed to reflect time-varying traffic conditions. Dynamic traffic characteristics are reflected through traffic volume and travel time, simulated from simulation models. Numerical experiments are conducted in the Kaohsiung City network. The results show that dynamic routes for hazmat transportation vary with respect to traffic flow conditions. The discussions of this research are expected to provide some insights into policy implications.
AB - After a series of gas pipeline explosions in Kaohsiung City, Taiwan, in 2014, the Environmental Protection Administration (EPA) issued regulations in 2017 requiring all chemical tank trucks to be equipped with GPS for real-time monitoring and control. Hazmat transportation problems, along with solution algorithms and applications, have been studied extensively. However, most of the research has focused on the route planning level. Dynamic characteristics should be incorporated to reflect possible dynamic traffic situations with more advanced information and communication capabilities for chemical tank trucks. This research formulates a bi-objective dynamic model and proposes a solution algorithm based on a genetic algorithm (GA) for dynamic hazmat route optimization. A dynamic bi-objective model, including transportation cost and risk, is developed to reflect time-varying traffic conditions. Dynamic traffic characteristics are reflected through traffic volume and travel time, simulated from simulation models. Numerical experiments are conducted in the Kaohsiung City network. The results show that dynamic routes for hazmat transportation vary with respect to traffic flow conditions. The discussions of this research are expected to provide some insights into policy implications.
UR - http://www.scopus.com/inward/record.url?scp=85141807571&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85141807571&partnerID=8YFLogxK
U2 - 10.1177/03611981221092002
DO - 10.1177/03611981221092002
M3 - Chapter
AN - SCOPUS:85141807571
VL - 2676
SP - 160
EP - 170
BT - Transportation Research Record
PB - SAGE Publications Ltd
ER -