Assessing Vulnerability of Transportation Networks for Disaster Response Operations

Cantillo, Víctor; Macea, Luis F.; Jaller, Miguel

doi:10.1007/s11067-017-9382-x

Cited by 44 publications

(15 citation statements)

References 56 publications

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“…Moreno et al [ 11 ] presented a novel model to optimize location, transportation, and fleet sizing for emergency logistics with considering deprivation costs. Cantillo et al [ 12 ] assessed transportation network vulnerability from logistical costs and deprivation costs. Zhu et al [ 13 ] studied the emergency relief routing optimization problem considering injured degree and deprivation cost.…”

Section: Introductionmentioning

confidence: 99%

[Retracted] A Novel Hybrid Algorithm for Multiobjective Location‐Allocation Problem in Emergency Logistics

Chu

Chen

2021

Computational Intelligence and Neuroscience

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Increased frequency of disasters keeps reminding us of the importance of effective resource distribution in postdisaster. To reduce the suffering of victims, this paper focuses on how to establish an effective emergency logistics system. We first propose a multiobjective optimization model in which the location and allocation decisions are made for a three-level logistics network. Three objectives, deprivation costs, unsatisfied demand costs, and logistics cost, are adopted in the proposed optimization model. Several cardinality and flow balance constraints are considered simultaneously. Then, we design a novel effective IFA-GA algorithm by combining the firefly algorithm and genetic algorithm to solve this complex model effectively. Furthermore, three schemes are proposed to improve the effectiveness of the IFA-GA algorithm. Finally, the numerical results provide several insights on the theory and practice of relief distribution, which also illustrate the validity of the proposed solution algorithm.

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Section: Introductionmentioning

confidence: 99%

[Retracted] A Novel Hybrid Algorithm for Multiobjective Location‐Allocation Problem in Emergency Logistics

Chu

Chen

2021

Computational Intelligence and Neuroscience

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“…The socio-economic dimension of resilience and vulnerability requires that we analyze the conflicting interests of stakeholders. In particular, we must study the 1 Examples of systems studied from this perspective are transportation networks (Cantillo et al 2018;Tamvakis and Xenidis 2012), urban systems (Östh et al 2018) and electrical power systems (Holmgren 2007) among others. 2 This broad definition of social-ecological systems includes spatial economic systems, for the latter represent the spatial dimension of production and consumption (Nijkamp and Ratajczak 2013), which weave together social and natural elements.…”

Section: Introductionmentioning

confidence: 99%

Vulnerability, Resilience and ‘Systemic Interest’: a Connectivity Approach

Cardinale

2019

Netw Spat Econ

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This paper analyzes the socioeconomic dimension of vulnerability and resilience from the viewpoint of connectivity. While no consensus has yet emerged on the definitions of vulnerability and resilience or on their relationship, it has been recognized that both have an important normative dimension, in that whether a system is considered vulnerable or resilient depends on the interests of the stakeholders involved. The paper proposes a dimension of resilience and vulnerability that is likely to be shared across a significant spectrum of stakeholders. To do so, the paper analyses connectivity within social-ecological systems from a BStructural Political Economy^viewpoint. A key concept in this regard is Bsystemic interest^, which is defined as the interest of stakeholders in keeping viable the system of connections within which they act. Systemic interest has desirable properties to conceptualize the normative dimension of vulnerability and resilience and leads to problematize their link with connectivity. In fact, it raises the question of what features of connectivity can be expected to lead to systemic interest, and how this impinges on vulnerability and resilience in different contexts. On the one hand, one might expect that a more interconnected system is more vulnerable to shocks, which propagate more easily throughout the system. On the other hand, such system might have a stronger systemic interest, so that a shock would trigger stakeholders' reaction to counteract its effects and avoid systemic consequences. The paper points to the institutional conditions that might make either outcome more likely in any given context.

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“…Several measures of impact assessment have been introduced in the past, looking at different indicators based on generalized costs, user costs, efficiency measures, network topological features and congestion effects (e.g. Taylor et al 2006;Jenelius et al 2006;Scott et al 2006;Sullivan et al 2009Sullivan et al , 2010Qiang and Nagurney 2012;Balijepalli and Oppong 2014;Xiaofei et al 2015;Rupi et al 2015;Cantillo et al 2019). In Taylor et al (2006), generalized costs -a measure of disutility of travel, such as distance, time or money -are used to estimate the impacts of network degradation for a very simplified model of the Australian road network.…”

Section: Introductionmentioning

confidence: 99%

Bridge closure in the road network of Lombardy: a spatio-temporal analysis of the socio-economic impacts

et al. 2022

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This paper introduces a methodology to evaluate the socio-economic impacts of closure for maintenance of one or more infrastructures of a large and complex road network. Motivated by a collaboration with Regione Lombardia, we focus on a subset of bridges in the region, although we aim at developing a method scalable to all road infrastructures of the regional network, consisting of more than 10,000 tunnels, bridges and overpasses. The final aim of the endeavor is to help decision-makers in prioritizing their interventions for maintaining and repairing infrastructure segments. We develop two different levels of impact assessment, both providing a unique global score for each bridge closure and investigating its spatio-temporal effects on mobility. We take advantage of a functional data analysis approach enhanced by a complex network theory perspective, thus modelling the roads of Lombardy as a network in which weights attributed to the edges are functional data. Results reveal the most critical bridges of Lombardy; moreover, for each bridge closure, the most impactful hours of the day and the most impacted municipalities of the region are identified. The proposed approach develops a flexible and scalable method for monitoring infrastructures of large and complex road networks.

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Assessing Vulnerability of Transportation Networks for Disaster Response Operations

Cited by 44 publications

References 56 publications

[Retracted] A Novel Hybrid Algorithm for Multiobjective Location‐Allocation Problem in Emergency Logistics

[Retracted] A Novel Hybrid Algorithm for Multiobjective Location‐Allocation Problem in Emergency Logistics

Vulnerability, Resilience and ‘Systemic Interest’: a Connectivity Approach

Bridge closure in the road network of Lombardy: a spatio-temporal analysis of the socio-economic impacts

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