A Bayesian decision model with hurricane forecast updates for emergency supplies inventory management

Taskin, Selda; Lodree, Emmett J.

doi:10.1057/jors.2010.14

Cited by 51 publications

(20 citation statements)

References 23 publications

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“…Lodree and Taskin (2009) and Taskin and Lodree (2011) use a Bayesian decision model with hurricane wind speed updates to manage inventories in a serial supply chain. The latter paper generalizes the former by considering a multiple, rather than a single, retailer supply chain and uses the NHC's official tropical cyclone wind speed probabilities.…”

Section: Literature Reviewmentioning

confidence: 99%

Supporting hurricane inventory management decisions with consumer demand estimates

Morrice

Cronin

Tanrısever

et al. 2016

J of Ops Management

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Matching supply and demand can be very challenging for anyone attempting to provide goods or services during the threat of a natural disaster. In this paper, we consider inventory allocation issues faced by a retailer during a hurricane event and provide insights that can be applied to humanitarian operations during slow-onset events. We start with an empirical analysis using regression that triangulates three sources of information: a large point-of-sales data set from a Texas Gulf Coast retailer, the retailer's operational and logistical constraints, and hurricane forecast data from the National Hurricane Center (NHC). We establish a strong association between the timing of the hurricane weather forecast, the forecasted landfall position of the storm, and hurricane sales. Storm intensity is found to have a weaker association on overall inventory decisions. Using the results of the empirical analysis and the NHC forecast data, we construct a state-space model of demand during the threat of a hurricane and develop an inventory management model to satisfy consumer demand prior to a hurricane making landfall. Based on the structure of the problem, we model this situation as a two-stage, two-location inventory allocation model from a centralized distribution center that balances transportation, shortage and holding costs. The model is used to explore the role of recourse, i.e., deferring part of the inventory allocation until observing the state of the hurricane as it moves towards landfall. Our approach provides valuable insights into the circumstances under which recourse may or may not be worthwhile in any setting where an anticipated extreme event drives consumer demand.

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Section: Literature Reviewmentioning

confidence: 99%

Supporting hurricane inventory management decisions with consumer demand estimates

Morrice

Cronin

Tanrısever

et al. 2016

J of Ops Management

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“…There are a number of articles focusing on different subtopics of aid chain flows. Some investigate the material procurement related issues (e.g., Campbell and Jones, 2011;Chang et al, 2010;Ertem et al, 2012); while others study inventory management and material distribution (e.g., Taskin and Lodree, 2011;Rottkemper et al, 2011).…”

Section: Flows and Distributionmentioning

confidence: 99%

“…For example, Taskin and Lodree (2011) incorporate a prediction model that has been used in a Bayesian decision framework to solve complex decision solutions made in response to an observed tropical cyclone. Their model helps address problems such as determining the appropriate quantities of emergency supplies that should be stockpiled at various locations.…”

Section: Flows and Distributionmentioning

confidence: 99%

Research in Humanitarian Supply Chain Management and a New Framework

Yalcin

Özpolat

et al. 2015

EJBE

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“…While the method is simple, it allows us to represent earthquake risk effectively. There are several studies in the literature that propose disaster preparedness models incorporating the unique aspects of the disasters; e.g., Taskin and Lodree (2011) and Galindo and Batta (2013) consider the dynamic wind speed and intensity information for hurricane preparedness and Garrido et al (2015) use a flood forecasting method to characterize flood risk. This study will be the first one to utilize risk assessment tools from the earthquake forecasting literature and incorporate them into optimization models to support disaster preparedness.…”

Section: Introductionmentioning

confidence: 99%

Disaster preparedness using risk-assessment methods from earthquake engineering

Battarra

Balcik

2018

European Journal of Operational Research

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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 from Turkey, a country under significant earthquake risk. We also present a case study that illustrates the implementation of our method to solve the inventory allocation problem of the Turkish Red Crescent.

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A Bayesian decision model with hurricane forecast updates for emergency supplies inventory management

Cited by 51 publications

References 23 publications

Supporting hurricane inventory management decisions with consumer demand estimates

Supporting hurricane inventory management decisions with consumer demand estimates

Research in Humanitarian Supply Chain Management and a New Framework

Disaster preparedness using risk-assessment methods from earthquake engineering

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