2018
DOI: 10.1016/j.ejor.2018.02.014
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Disaster preparedness using risk-assessment methods from earthquake engineering

Abstract: Analyzing the uncertainties associated with disaster occurrences is critical to make effective disaster preparedness plans. In this study, we focus on pre-positioning emergency supplies for earthquake preparedness. We present a new method to compute earthquake likelihood and the number of the affected people. Our approach utilizes forecasting methods from the earthquake engineering literature, and avoids using any probabilistic scenarios. We validate the proposed technique by using historical earthquake data f… Show more

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Cited by 38 publications
(15 citation statements)
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“…They evaluate their proposed inventory planning strategies and forecasting methods for dynamic lead time prediction. Battara, Balcik, and Xu (2018) propose a risk assessment method to compute earthquake likelihood and the number of affected individuals after a potential earthquake using forecasting methods. Garvey, Carnovale, and Yeniyurt (2015) propose a Bayesian network approach and develop a model of risk propagation in a supply network that considers inter‐dependencies among different risk types considered.…”
Section: Application Fieldsmentioning
confidence: 99%
See 2 more Smart Citations
“…They evaluate their proposed inventory planning strategies and forecasting methods for dynamic lead time prediction. Battara, Balcik, and Xu (2018) propose a risk assessment method to compute earthquake likelihood and the number of affected individuals after a potential earthquake using forecasting methods. Garvey, Carnovale, and Yeniyurt (2015) propose a Bayesian network approach and develop a model of risk propagation in a supply network that considers inter‐dependencies among different risk types considered.…”
Section: Application Fieldsmentioning
confidence: 99%
“…For example, predicting geospatial spread of diseases (predictive) for better resource allocation (prescriptive) is critical for pandemic response (Araz, Lant, Jehn, & Fowler, 2013; Huang et al., 2017); understanding emerging trends in consumer behavior during natural disasters such as hurricanes is critical for optimal inventory management (Morrice, Cronin, Tanrisever, & Butler, 2016). Other examples can be found in analyzing social networks and predicting the role of social media on public behavior (Morss, Cuite, Demuth, Hallman, & Shwom, 2018), managing traffic flows during catastrophic events (Tuydes‐Yaman & Ziliaskopoulos, 2014), and optimizing location of relief facilities for maximum coverage and safety (Salman & Yücel, 2015; Battara et al., 2018; Choi et al., 2018). Operations in supply chains are directly affected by these events and can be disrupted, which then would increase the severity of these events not only economically, but also in terms of number of lives and regions at risk (Apte, Khawam, Regnier, & Simon, 2016; Jahre et al., 2016).…”
Section: Analytics Techniquesmentioning
confidence: 99%
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“…Los terremotos han causado históricamente daños y pérdidas humanas destacadas en Europa. Además, los terremotos ocurridos en Europa a principios del siglo XX han costado alrededor de 29 mil millones de euros y han causado 19 000 bajas (Battarra et al, 2018). El potencial destructivo de un terremoto depende del daño producido, de la preparación y de la resiliencia de la población.…”
Section: Abreviaturasunclassified
“…Among existing natural disasters, earthquakes have historically caused the most outstanding damage and human losses in Europe. Moreover, earthquakes occurred in Europe during the early 20th century have cost around 29 billion euros and have caused 19,000 casualties [1]. The destructive potential of an earthquake depends on the damage produced, the preparation and the resilience of the population.…”
Section: Introductionmentioning
confidence: 99%