Determining the Optimal Location of Terror Response Facilities Under the Risk of Disruption

Meng, Lingpeng; Kang, Qi; Han, Chuanfeng; Zhou, MengChu

doi:10.1109/tits.2017.2697965

Cited by 34 publications

(27 citation statements)

References 48 publications

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“…We show that the proposed model in this paper is more reliable than Meng et al. (2017) under facility risk and malicious attacks.…”

Section: Related Workmentioning

confidence: 55%

“…Meng et al. (2017) develop a mixed integer programming formulation for the location of terror response facilities and employ the “level‐r” assignment to address the unexpected facility disruption. Another strand of literature managing the risk of disruption is the fortification of reliability for existing facilities focusing on the resource allocation in the existing network.…”

Section: Related Workmentioning

confidence: 99%

“…As the strategic interactions between the defender and the attacker are interdependent, their individual responses cannot be analyzed as though one side is passive. To this end, game theory is used to model these strategic, interdependent interactions for integrating the risk of disruption of facilities (Meng et al., 2017).…”

Section: Introductionmentioning

confidence: 99%

“…Note that their concentration is on the resource allocation while the necessity of network design stage against the strategic attacker should be paid attention to in the light of Aksen and Aras (2013) and Meng et al. (2017). In this paper, we will concentrate on the location of terror response facility integrating disruption risk with hidden information, which makes the anti‐terrorism facility system more reliable.…”

Section: Introductionmentioning

confidence: 99%

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A game‐theoretic approach for the location of terror response facilities with both disruption risk and hidden information

Gan

et al. 2020

Int Trans Operational Res

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Recently, locating emergency response facilities has been drawing increasing attention with the highly strategic nature of terrorist attacks. To this end, we present a game‐theoretic approach for the location of terror response facilities when both disruption risk and hidden information are taken into account. The game is described as a two‐stage game, in which the first stage allows the State, that is, defender, to locate the terror response facilities, including disclosed and undisclosed facilities, and assign them to the attacked city, while the second stage allows the terrorist, that is, attacker, to select one city to attack with partial information about facility location and assignment. We propose a mixed integer bi‐level nonlinear programming formulation, and in response, a heuristic algorithm is developed to find the equilibrium solution. Extensive computational tests on both synthetic data and a real‐world dataset of provincial capital cities in China demonstrate the effectiveness of the developed algorithm.

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“…We show that the proposed model in this paper is more reliable than Meng et al. (2017) under facility risk and malicious attacks.…”

Section: Related Workmentioning

confidence: 55%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A game‐theoretic approach for the location of terror response facilities with both disruption risk and hidden information

Gan

et al. 2020

Int Trans Operational Res

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“…Cavdur et al in [16] has deliberated on a facility location problem for disaster operation management, and the proposed approach for solution is based on a deterministic model. Meng et al determine the optimal location facilities for the terrorist attack in terms of emergency response in [17]. The study however contains the assumptions of boundless limitations, which are not practical.…”

Section: Introductionmentioning

confidence: 99%

Disaster Mitigation in Urban Pakistan Using Agent Based Modeling with GIS

Maqbool

Usmani

Afzal

et al. 2020

IJGI

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This study aims to propose an application of agent based modeling (ABM) and simulation for disaster mitigation in an urban region of Pakistan. Pakistan has been working over the past few decades to reduce the risk factor of disasters by using different disaster management approaches. However, these efforts are in an early stage. Although lack of planning and unchecked urbanization are the main hurdles, insufficient resources in terms of technology is also a major contributing factor that impedes achieving desired results. In this paper, we are proposing ABM and simulation of approaches using geographical information system (GIS) maps for disaster management in the urban locality of Pakistan. The conceptual model was implemented for analysis of resource allocation (RA) of first response units (ambulances, fire brigade, etc.). In the proposed model, we used two allocation algorithms; high severity level (HSL) and first come first serve (FCFS). These algorithms were simulated in NetLogo by creating a hypothetical disaster scenario in Rawalpindi city. In our experiments, the design was based on demand, resource agents, and their allocation behavior for disaster management. We analyzed the resource allocation mechanism using average wait time, overall number of demands, execution time, and unallocated demands as performance measures.

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Vulnerability cloud: A novel approach to assess the vulnerability of critical infrastructure systems

Meng

Yao

Chen

et al. 2022

Concurrency and Computation

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Critical infrastructures provide citizens with lifeline functions such as water, electricity and energy and so forth. These interdependent infrastructure systems require reliable models for vulnerability measurement and topological controllability against usual disruptions and unusual hazards. This article proposes a novel approach, named vulnerability cloud, to describe vulnerability distribution and assess the vulnerability of critical infrastructure systems. A vulnerability distribution network is developed for simulation of negative impact on each node, with which the results are represented in vulnerability cloud by three metrics of vulnerability. The vulnerability cloud of single-service and multiservice infrastructure system are proposed, respectively. This approach is applied to a case study of "electric-gas" interdependent critical infrastructure system. Results show that a node's vulnerability and serviceability is closely related to the node's degree, especially the out-degree, while overall system's vulnerability is greatly affected by descent rate of coverage of each infrastructural service node. This approach, at the same time, generates probabilistic simulation diagrams to show continuous vulnerability distribution in areas covered by the specified critical infrastructure systems.

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Determining the Optimal Location of Terror Response Facilities Under the Risk of Disruption

Cited by 34 publications

References 48 publications

A game‐theoretic approach for the location of terror response facilities with both disruption risk and hidden information

A game‐theoretic approach for the location of terror response facilities with both disruption risk and hidden information

Disaster Mitigation in Urban Pakistan Using Agent Based Modeling with GIS

Vulnerability cloud: A novel approach to assess the vulnerability of critical infrastructure systems

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