A survey on hazardous materials accidents during road transport in China from 2000 to 2008

Yang, Jie; Li, Fengying; Zhou, Jianliang; Zhang, Ling; Huang, Lei; Bi, Jun

doi:10.1016/j.jhazmat.2010.08.085

Cited by 132 publications

(99 citation statements)

References 25 publications

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“…In addition of accident probability distributions, the link consequence distributions can be specified according to the severity levels of hazmat accidents, population density in the neighborhood of the links, and the region of exposure. In many recent works, these criteria are considered for estimating accident consequences and risks (Iosjpe et al 2009;Georgiadou et al 2010;Yang et al 2010;Chakrabarti and Parikh 2011a;Bonvicini et al 2012;Das et al 2012). We evaluated accident severities based on the following formula:…”

Section: Network Informationmentioning

confidence: 99%

Dynamic conditional value-at-risk model for routing and scheduling of hazardous material transportation networks

2015

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This paper illustrates a dynamic model of conditional value-at-risk (CVaR) measure for risk assessment and mitigation of hazardous material transportation in supply chain networks. The well-established market risk measure, CVaR, which is commonly used by financial institutions for portfolio optimizations, is investigated. In contrast to previous works, we consider CVaR as the main objective in the optimization of hazardous material (hazmat) transportation network. In addition to CVaR minimization and route planning of a supply chain network, the time scheduling of hazmat shipments is imposed and considered in the present study. Pertaining to the general dynamic risk model, we analyzed several scenarios involving a variety of hazmats and time schedules with respect to optimal route selection and CVaR minimization. A solution algorithm is then proposed for solving the model, with verifications made using numerical examples and sensitivity analysis.

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Section: Network Informationmentioning

confidence: 99%

Dynamic conditional value-at-risk model for routing and scheduling of hazardous material transportation networks

2015

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“…As an illustrative example, five experts presented their points of view for four components of risk by linguistic variables for edge (14,15) which indicates the link (Polefasa, Sarvestan) in the network shown in Table 4. Node codes and their names are available in Appendix A. Triangular fuzzy numbers (TFN) of variables are also presented in the next rows of table according to Table 2.…”

Section: Case Study and Experimental Datamentioning

confidence: 99%

“…Dependency of travel time and risk associated to road network upon road traffic measures [6], road geometric designs [7,4], weather condition [8] and safety regulations which are imposed on drivers and transport companies [9] are also known as attributes in Hazmat routing problems. Population [5,10,11], environment [8,[11][12][13] and accident [1,5,7,9,14] are the main apprehensions to define risk associated with Hazmat incident impacts. Specified regional networks which have been assigned by local authorities for Hazmat transportation, particularly for better enforcement and improving road safety, lead researchers to solve Hazmat routing problem [15][16][17][18] under network constraints.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, the nature of hazardous materials [4,19] together with public security [17] have also been studied as important attributes in this area. Management issues such as road network and vehicle capacity planning [10,20], Hazmat delivery time [1,7], and eventually emergency response have been considered in the above problem [5,12,14,19].…”

Section: Introductionmentioning

confidence: 99%

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Developing a chaotic pattern of dynamic Hazmat routing problem

Mahmoudabadi¹,

Seyedhosseini²

2014

IATSS Research

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The present paper proposes an iterative procedure based on chaos theory on dynamic risk definition to determine the best route for transporting hazardous materials (Hazmat). In the case of possible natural disasters, the safety of roads may be seriously affected. So the main objective of this paper is to simultaneously improve the travel time and risk to satisfy the local and national authorities in the transportation network. Based on the proposed procedure, four important risk components including accident information, population, environment, and infrastructure aspects have been presented under linguistic variables. Furthermore, the extent analysis method was utilized to convert them to crisp values. To apply the proposed procedure, a road network that consists of fifty nine nodes and eighty two-way edges with a pre-specified affected area has been considered. The results indicate that applying the dynamic risk is more appropriate than having a constant risk. The application of the proposed model indicates that, while chaotic variables depend on the initial conditions, the most frequent path will remain independent. The points that would help authorities to come to the better decision when they are dealing with Hazmat transportation route selection.

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“…Many papers have discussed on road accidents field. For example, Yang et al [11] carried out a study of 322 accidents that occurred during the road transport of hazardous materials (hazmat) in China from 2000 to 2008. Coll et al [12] contributed the ongoing research effort on the estimation of road safety composite index for hotspots' identification and ranking.…”

Section: Introductionmentioning

confidence: 99%

Ranking of causes lead to road accidents using a new linguistic variable in interval type-2 fuzzy entropy weight of a decision making method

Zamri¹,

Abdullah²

2014

AIP Conference Proceedings

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A survey on hazardous materials accidents during road transport in China from 2000 to 2008

Cited by 132 publications

References 25 publications

Dynamic conditional value-at-risk model for routing and scheduling of hazardous material transportation networks

Dynamic conditional value-at-risk model for routing and scheduling of hazardous material transportation networks

Developing a chaotic pattern of dynamic Hazmat routing problem

Ranking of causes lead to road accidents using a new linguistic variable in interval type-2 fuzzy entropy weight of a decision making method

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