Decomposition of general facility disruption correlations via augmentation of virtual supporting stations

Xie, Siyang; Li, Xiaopeng; Ouyang, Yanfeng

doi:10.1016/j.trb.2015.06.006

Cited by 36 publications

(9 citation statements)

References 14 publications

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“…ey presented some asymptotic results using a scenario-based method. Xie et al [17] proposed a methodological framework for decomposing general correlated facility disruptions. Any type of correlation can be transformed into an augmented network problem by this methodology.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimization Model Based on Reachability Guarantee for Emergency Facility Location and Link Reinforcement

Liu

2020

Journal of Advanced Transportation

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The reasonable location of emergency facilities plays an important role in both predisaster service and postdisaster relief. Moreover, damage to the transportation network often affects the accessibility of demand points, which can seriously hamper timely rescue operations. Reasonable location of emergency facilities and reinforcement of fragile roads are two important strategies to improve the reachability of demand points. In this paper, we proposed a biobjective optimization model to determine locations of emergency facilities and links to be reinforced given a limited budget. Each demand point is allocated a primary facility and a backup facility, the former can provides normal service, and the latter is prepared for postdisaster relief. One goal of the model is to minimize the operating cost of normal services, and another goal is to maximize the reachability guarantee of demand points. The novelty and contribution of this paper are that we defined the reachability by introducing damage tolerance instead of link failure probability. Based on this, we defined the reachability guarantee to deal with the worst scenario of disasters. By embedding the max-flow problem of the reachability guarantee into the emergency facility location problem, the locations of emergency facilities and links to be reinforced can be determined simultaneously. The methodology is applied to a simplified Sioux Falls transportation network. Results such as the trade-off curve of two goals, budget efficiency, and the effect of reinforcement demonstrated the effectiveness of the model.

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Section: Literature Reviewmentioning

confidence: 99%

Optimization Model Based on Reachability Guarantee for Emergency Facility Location and Link Reinforcement

Liu

2020

Journal of Advanced Transportation

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“…Methodologies for solving the problem have also been proposed using Lagrangian Relaxation and heuristics ( Fisher, 2004;Geoffrion and Bride, 1978;Holmberg et al, 1999;Mulvey and Crowder, 1979;Nascimento et al, 2012 ) and meta-heuristics ( Chiou and Lan, 2001;Handl and Knowles, 2007 ). Recently, the facility location problem with stochastic disruptions has been an active area of research Cui et al, 2010;Qi et al, 2010;Snyder and Daskin, 2005;Xie et al, 2015 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Network based temporary facility location for the Emergency Medical Services considering the disaster induced demand and the transportation infrastructure in disaster response

Chen

2016

Transportation Research Part B: Methodological

107

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“…Moreover, efforts have been made to build more resilient systems (e.g., facility location and design chosen to optimize reliable service) based on an understanding of the interdependencies. For example, Wang and Ouyang (2013) describe the geographical interdependencies of demand among facilities and developed game-theoretic models to find an optimal spatial distribution of service facilities; Xie, et al (2015) proposed a novel network augmentation approach that has a proven ability to decompose any infrastructure disruption interdependencies, such that the optimal design problem can be formulated and solved equivalently with only independent disruptions.…”

Section: Previous Workmentioning

confidence: 99%

Assessing Socioeconomic Impacts of Cascading Infrastructure Disruptions in a Dynamic Human-Infrastructure Network

Lu¹,

Wang²,

Wang³

et al. 2016

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The functionality of modern cities relies heavily on interdependent infrastructure systems such as those for water, power, and transportation. Disruptions often propagate within and across physical infrastructure networks and result in catastrophic consequences. The reaction of communities to disasters (e.g., seeking alternatives) may further transfer and aggravate the burden on surviving infrastructures, which may facilitate cascading secondary disruptions. Hence, a holistic analysis framework that integrates infrastructure interdependencies and community behaviors is needed to evaluate a city's vulnerability to disruptions and to assess the impact of a disaster. U.S. Army doctrine requires that commanders understand, visualize, and describe the infrastructure component of the Joint Operating Environment to accomplish the Army's missions of protecting, restoring, and developing infrastructure. To this end, a game-theoretical equilibrium model has been developed in a multilayer infrastructure network, to systematically investigate the mutual influence between the infrastructures and the communities. In this model, two types of infrastructure failure patterns are formulated to capture general network interdependencies; network equilibrium is extended into infrastructure and community systems to address redistribution of demand for life-supporting resources; the societal impact of disasters is estimated based on resource demand loss, cost increase, and total infrastructure failure. A real-world case study was implemented to demonstrate the proposed model and algorithm, and to reveal insights.

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Decomposition of general facility disruption correlations via augmentation of virtual supporting stations

Cited by 36 publications

References 14 publications

Optimization Model Based on Reachability Guarantee for Emergency Facility Location and Link Reinforcement

Optimization Model Based on Reachability Guarantee for Emergency Facility Location and Link Reinforcement

Network based temporary facility location for the Emergency Medical Services considering the disaster induced demand and the transportation infrastructure in disaster response

Assessing Socioeconomic Impacts of Cascading Infrastructure Disruptions in a Dynamic Human-Infrastructure Network

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