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

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Title: A Bayesian decision model with hurricane forecast updates for emergency supplies inventory management.
Authors: Taskin, S.1 STaskin@aselsan.com.tr, Lodree, E. J.2 eldree@auburn.edu
Source: Journal of the Operational Research Society. Jun2011, Vol. 62 Issue 6, p1098-1108. 11p.
Subjects: Hurricanes, Bayesian analysis, Prediction models, Emergency management, Cost effectiveness, Inventory control, National Hurricane Center
Abstract: Hurricane forecasts are intended to convey information that is useful in helping individuals and organizations make decisions. For example, decisions include whether a mandatory evacuation should be issued, where emergency evacuation shelters should be located, and what are the appropriate quantities of emergency supplies that should be stockpiled at various locations. This paper incorporates one of the National Hurricane Center's official prediction models into a Bayesian decision framework to address complex decisions made in response to an observed tropical cyclone. The Bayesian decision process accounts for the trade-off between improving forecast accuracy and deteriorating cost efficiency (with respect to implementing a decision) as the storm evolves, which is characteristic of the above-mentioned decisions. The specific application addressed in this paper is a single-supplier, multi-retailer supply chain system in which demand at each retailer location is a random variable that is affected by the trajectory of an observed hurricane. The solution methodology is illustrated through numerical examples, and the benefit of the proposed approach compared to a traditional approach is discussed. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:Hurricane forecasts are intended to convey information that is useful in helping individuals and organizations make decisions. For example, decisions include whether a mandatory evacuation should be issued, where emergency evacuation shelters should be located, and what are the appropriate quantities of emergency supplies that should be stockpiled at various locations. This paper incorporates one of the National Hurricane Center's official prediction models into a Bayesian decision framework to address complex decisions made in response to an observed tropical cyclone. The Bayesian decision process accounts for the trade-off between improving forecast accuracy and deteriorating cost efficiency (with respect to implementing a decision) as the storm evolves, which is characteristic of the above-mentioned decisions. The specific application addressed in this paper is a single-supplier, multi-retailer supply chain system in which demand at each retailer location is a random variable that is affected by the trajectory of an observed hurricane. The solution methodology is illustrated through numerical examples, and the benefit of the proposed approach compared to a traditional approach is discussed. [ABSTRACT FROM AUTHOR]
ISSN:01605682
DOI:10.1057/jors.2010.14