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A Bayesian decision model with hurricane forecast updates for emergency supplies inventory management / Taskin, S. in Journal of the operational research society (JORS), Vol. 62 N° 6 (Juin 2011) 

Public ISBD [article]  in Journal of the operational research society (JORS) > Vol. 62 N° 6 (Juin 2011) . - pp. 1098–1108 Titre : A Bayesian decision model with hurricane forecast updates for emergency supplies inventory management Type de document : texte imprimé Auteurs : Taskin, S., Auteur ; Lodree, E. J., Auteur Année de publication : 2011 Article en page(s) : pp. 1098–1108 Note générale : Recherche opérationnelle Langues : Anglais (eng) Mots-clés : Disaster  preparedness  Hurricane  prediction  Humanitarian  relief  Inventory  control  Supply  chain  management  Bayesian  decision  theory Index. décimale : 001.424 Résumé : 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. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n6/abs/jors201014a.html [article] A Bayesian decision model with hurricane forecast updates for emergency supplies inventory management [texte imprimé] / Taskin, S., Auteur ; Lodree, E. J., Auteur . - 2011 . - pp. 1098–1108. Recherche opérationnelle Langues : Anglais (eng) in Journal of the operational research society (JORS) > Vol. 62 N° 6 (Juin 2011) . - pp. 1098–1108 Mots-clés : Disaster  preparedness  Hurricane  prediction  Humanitarian  relief  Inventory  control  Supply  chain  management  Bayesian  decision  theory Index. décimale : 001.424 Résumé : 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. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n6/abs/jors201014a.html