2023
DOI: 10.3390/app13116608
|View full text |Cite
|
Sign up to set email alerts
|

Optimal Location of Emergency Facility Sites for Railway Dangerous Goods Transportation under Uncertain Conditions

Abstract: Railroad accidents involving dangerous goods (DG) need to be rescued quickly due to their hazardous nature. This paper proposes an emergency facility location model for the railway dangerous-goods transportation problem (RDGT-EFLP, abbreviated as EFLP). The EFLP model is based on an ellipsoidal robust model that introduces a robust control safety parameter Ω to measure the risk preferences of decision makers and limits the range of uncertain demand, the range of uncertain service and the range of safety parame… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
2
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
2
1

Relationship

0
3

Authors

Journals

citations
Cited by 3 publications
(2 citation statements)
references
References 37 publications
0
2
0
Order By: Relevance
“…Aiming at the multi-objective programming model, Wang et al [10] established a mixed integer model of uncertainty, and designed a location problem that could be solved by combining particle swarm optimization algorithm and variable domain search algorithm with factors such as time cost, penalty cost of lack of resources, alternative sources of resources from suppliers and emergency warehouses, different modes of transportation and multiple resource types. In addition, Wang et al [11] designed a robust model based on ellipsoid. In the uncertain demand range, uncertain service range and security parameter range, the emergency location solution is found, and the genetic algorithm is used to solve it.…”
Section: Introductionmentioning
confidence: 99%
“…Aiming at the multi-objective programming model, Wang et al [10] established a mixed integer model of uncertainty, and designed a location problem that could be solved by combining particle swarm optimization algorithm and variable domain search algorithm with factors such as time cost, penalty cost of lack of resources, alternative sources of resources from suppliers and emergency warehouses, different modes of transportation and multiple resource types. In addition, Wang et al [11] designed a robust model based on ellipsoid. In the uncertain demand range, uncertain service range and security parameter range, the emergency location solution is found, and the genetic algorithm is used to solve it.…”
Section: Introductionmentioning
confidence: 99%
“…This study is crucial in the context of environmental sustainability and provides insights into reducing emissions, making urban rail transit more eco-friendly. Wang et al [5] addressed the critical issue of safety in railway transportation, particularly regarding the transport of dangerous goods. The study focused on identifying optimal locations for emergency facilities to effectively respond to uncertain conditions, significantly contributing to the mitigation of potential risks.…”
mentioning
confidence: 99%