Fuzzy integrated vulnerability assessment model for critical facilities in combating the terrorism

Akgün, İlker; Kandakoğlu, Ahmet; Özok, Ahmet Fahri

doi:10.1016/j.eswa.2009.10.035

Cited by 60 publications

(19 citation statements)

References 28 publications

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“…As a result, fuzzy methods or methods using the rough set theory must be adopted (Greco et al, 2001). The article written by Akgun et al (2010) presents an interesting model that examines the vulnerability of critical infrastructure's elements, including airports, to terrorist attacks. The proposed approach is referred to as the fuzzy integrated vulnerability assessment model (FIVAM).…”

Section: Literature Reviewmentioning

confidence: 99%

A fuzzy model for evaluating airport security screeners' work

Skorupski

Uchroński

2015

Journal of Air Transport Management

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Section: Literature Reviewmentioning

confidence: 99%

A fuzzy model for evaluating airport security screeners' work

Skorupski

Uchroński

2015

Journal of Air Transport Management

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“…Among these models, there are several studies considering MCDM/A approaches (Akgun et al 2010;Sri Bhashyam and Montibeller 2012;Koonce et al 2008;Patterson and Apostolakis 2007).…”

Section: Risk Analysis On Counter-terrorismmentioning

confidence: 99%

“…In their paper, Akgun et al (2010) stress that assessing the vulnerability of critical assets (e.g. : airports, dams, chemical plants, nuclear power plants) to terrorist attacks is a highly complex strategic activity, requiring a methodology structured to support the decision-making process in defense planning.…”

Section: Risk Analysis On Counter-terrorismmentioning

confidence: 99%

Multidimensional Risk Analysis

Almeida

Cavalcante

Alencar

et al. 2015

International Series in Operations Research &Amp; Management Science

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Accidents involve critical consequences that require an appropriate and efficient form of risk management. A multidimensional risk analysis allows a broader view. MCDM/A approaches enable more consistent decision-making, taking into account the DM's rationality (compensatory or non-compensatory), DM's behavior regarding risk (prone, neutral or averse) and the uncertainties inherent in the risk context. This chapter presents numerical applications illustrating the use of multicriteria models in two different contexts: a natural gas pipeline and an underground electricity distribution system. Two different MCDM/A approaches are considered: MAUT (Multiattribute Utility Theory) and the ELECTRE TRI outranking method. In the numerical applications, MCDM/A approach steps for building decision models are presented: identifying hazard scenarios, estimating the set of payoffs, eliciting the MAU function (Multi-attribute Utility function), computing the probability function of consequences and estimating multidimensional risk. Loss functions are introduced in the models to calculate the probability distribution functions over the multiple criteria such as impact on humans, and environmental and financial losses. Therefore, Decision Theory concepts are applied to estimate risk in industrial plants and modes of transportation. Finally, other decision problems related to multidimensional risk analysis, using MCDM/A, are considered in different contexts, such as: power electricity systems, natural hazards, risk analysis on counter-terrorism, nuclear power plant. Justifying the Use of the Multidimensional RiskThe perceived level of risk is directly linked to the perceived intensity of consequences to people and society as well as to issues related to the level of probability. These consequences are multidimensional and are associated to the objectives, represented by criteria and can be approached with an MCDM/A or a multiobjective method (see Chap. 2). Many studies show that using a single dimension of risk may not be realistic (Morgan et al.

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“…It causes the necessity to use the fuzzy methods or those using the theory of rough sets (Bajpai et al, 2010;Tay and Lim, 2008a;Greco et al, 2001). In Akgun et al (2010) an interesting model was presented in which the vulnerability of critical infrastructure, which also includes airports, to terrorist attacks was examined. The proposed approach was called FIVAM (Fuzzy Integrated Vulnerability Assessment Model).…”

Section: Overview Of the State Of Researchmentioning

confidence: 99%