A numerical procedure for assessing risks from road transport of dangerous substances

Spadoni, Gigliola; Leonelli, P.; Verlicchi, Paola; Fiore, Roberta

doi:10.1016/0950-4230(95)00029-z

Cited by 21 publications

(8 citation statements)

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“…Table 2a. A classification of hazmat transportation models -risk assesment Road Jonkman et al, 2003;Nardini et al, 2003;Martinez-Alegria et al, 2003 G ;Rosmuller and Van Gelder, 2003;Abkowitz, 2002 C ;Fabiano et al, 2002;Kimberly and Killmer, 2002;Saccomanno and Haastrup, 2002 N ;Hollister, 2002;Hwang et al, 2001;Abkowitz et al, 2001;Verter and Kara, 2001 G ;Efroymson and Murphy, 2000;ICF Consulting, 2000;Leonelli et al, 2000;Zhang et al, 2000 G ;Pet-Armacost et al, 1999;Cassini, 1998;Mills and Neuhauser, 1998;Cutter and Ji, 1997;Groothuis and Miller, 1997;Lovett et al, 1997 G ;Pine and Marx, 1997;Alp and Zelensky, 1996;Ertugrul, 1995;Sissell, 1995;Chakraborty and Armstrong, 1995;Erkut and Verter, 1995a U ;Erkut and Verter, 1995b;Moore et al, 1995 G ;Spadoni et al, 1995;Verter and Erkut, 1995 U ;Gregory and Lichtenstein, 1994;Macgregor et al, 1994;Hobeika and Kim, 1993;Sandquist et al, 1993;Harwood et al, 1993;Abkowitz et al, 1992;Glickman, 1991;Grenney et al, 1990 DSS ;…”

Section: Classificationmentioning

confidence: 99%

Hazardous Materials Transportation

Verter

2011

Wiley Encyclopedia of Operations Research and Management Science

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Significant volumes of dangerous goods are transported by road, rail, and marine shipments. Accidental release of this cargo can be harmful to humans and the environment. Governments at different levels are responsible for protecting the public and the environment from the undesirable consequences of hazardous materials transportation. This introductory article provides a brief overview of the state of the art in hazardous materials transportation. To this end, the alternative transport modes for dangerous goods are discussed, the prevailing methodologies for transport risk assessment are highlighted and the risk mitigation policies available for regulators are underlined. The article also emphasizes that the transportation of hazardous materials through urban areas as well as the use of intermodal transport networks for dangerous goods shipments constitute two potentially fruitful avenues for future research.

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Section: Classificationmentioning

confidence: 99%

Hazardous Materials Transportation

Verter

2011

Wiley Encyclopedia of Operations Research and Management Science

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“…Logistics risk assessment is usually emphasised on risk analysis of hazardous material or dangerous goods transportation (Spadoni et al 1995;Zhang, Hodgson, and Erkut 2000;Scenna and Santa Cruz 2005;Verma 2011;Samvedi, Jain, and Chan 2013). In general, publications are considered to apply separately on road, rail, air, or sea (Spadoni et al 1995;Scenna and Santa Cruz 2005;Tsai and Su 2005;Verma 2011); however, a very limited number apply to multimodal logistics, particularly green logistics. According to the European Conference of Ministers of Transport, multimodal transport is the integration of two or more modes of transport to move passengers or goods from one source to a destination in a single contract (Kengpol, Meethom, and Tuominen 2012).…”

Section: Introductionmentioning

confidence: 99%

“…The analytic hierarchy process (AHP) can also be used in risk assessment with multiple criteria (Tsai and Su 2005;Wang, Liu, and Elhag 2008;Silvestri, De Felice, and Petrillo 2012). The combination of AHP and data envelopment analysis (DEA) proposed by Wang, Liu, and Elhag (2008) as a quantitative risk analysis can quantify risk level in multimodal logistics (Spadoni et al 1995).…”

Section: Introductionmentioning

confidence: 99%

The development of a decision support framework for a quantitative risk assessment in multimodal green logistics: an empirical study

Kengpol

Tuammee

2015

International Journal of Production Research

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The objective of this research was to develop a decision support framework (DSF) to assess quantitative risk in multimodal green logistics. This risk assessment is the combination of a number of models, the failure mode and effects analysis, the risk contour plot, the quantitative risk assessment, the analytic hierarchy process and the data envelopment analysis which can support a user to perform risk assessment in various decisions. The contribution of this research is that the risk assessment model can generate an optimal green logistics route in accordance with weight from the user. The highlight of this DSF is that the quantitative assessment model can reduce bias on risk assessment of logistics route. An in-depth case study, recommendations, limitations and further research are also provided.

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“…(6), the step of the normalized weight vector (N i ) is used to obtain the priority weight vector of each criteria by Eqs. (10)-(11). Thus, the minimum degree of possibility for each pairwise comparison is computed as:d (F ) = min V (F ≥ I, O, S, E) = 0.329 d (I) = min V (I ≥ F, O, S, E) = 0.398 d (O) = min V (O ≥ F, I, S, E) = 0.162 d (S) = min V (S ≥ F, I, O, E) = 0.075 d (E) = min V (E ≥ F, I, O, S) = 0.062Therefore, the weight vector is computed as W = (0.329, 0.398, 0.162, 0.075, 0.062).…”

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confidence: 99%

A Risk Analysis Based on a Two-Stage Model of Fuzzy AHP-DEA for Multimodal Freight Transportation Systems

et al. 2020

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Multimodal transportation has become a main focus of logistics systems due to environmental concerns, road safety issues, and traffic congestion. Consequently, research and policy interests in multimodal freight transportation problems are increasing. However, there are major challenges in the development of multimodal transportation associated with inherent risks and numerous uncertainties. Since risks are potential threats that directly impact logistics and transportation systems, comprehensive risk analysis should be carried out. Risk analysis is a critical process of identifying and analyzing significant issues to help industry mitigate those risks. However, identifying and prioritizing risks is more complex because of the ambiguity of the relevant data. This study proposes the integration of the fuzzy analytic hierarchy process (FAHP) and data envelopment analysis (DEA) for identifying and assessing quantitative risks. The proposed FAHP-DEA methodology uses the FAHP method to determine the weights of each risk criterion. The DEA method is employed to evaluate the linguistic variables and generate the risk scores. The simple additive weighting (SAW) method is used to aggregate risk scores under different risk criteria into an overall risk score. A case study of the coal industry demonstrates that the proposed risk analysis model is practical and allows users to more accurately prioritize risks while selecting an optimal multimodal transportation route. The process raises user's attention to the high-priority risks and is useful for industries in optimizing a multimodal transportation route under risk decision criteria. INDEX TERMS Multimodal freight transportation, logistics, optimal route, risk analysis, risk assessment, DEA, FAHP.

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A numerical procedure for assessing risks from road transport of dangerous substances

Cited by 21 publications

References 1 publication

Hazardous Materials Transportation

Hazardous Materials Transportation

The development of a decision support framework for a quantitative risk assessment in multimodal green logistics: an empirical study

A Risk Analysis Based on a Two-Stage Model of Fuzzy AHP-DEA for Multimodal Freight Transportation Systems

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