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Centralized vs. decentralized ambulance diversion / Sarang Deo in Management science, Vol. 57 N° 7 (Juillet 2011) 

Public ISBD [article]  in Management science > Vol. 57 N° 7 (Juillet 2011) . - pp. 1300-1319 Titre : Centralized vs. decentralized ambulance diversion : A network perspective Type de document : texte imprimé Auteurs : Sarang Deo, Auteur ; Gurvich Itai, Auteur Année de publication : 2011 Article en page(s) : pp. 1300-1319 Note générale : Management Langues : Anglais (eng) Mots-clés : Emergency  department  Ambulance  diversion  Game  theory  Queueing  networks Index. décimale : 658 Organisation des entreprises. Techniques du commerce Résumé : One of the most important operational challenges faced by emergency departments (EDs) in the United States is patient overcrowding. In periods of overcrowding, an ED can request the emergency medical services (EMS) agency to divert incoming ambulances to neighboring hospitals, a phenomenon known as “ambulance diversion.” The EMS agency may accept this request provided that at least one of the neighboring EDs is not on diversion. From an operations perspective, properly executed ambulance diversion should result in resource pooling and reduce the overcrowding and delays in a network of EDs. Recent evidence indicates, however, that this potential benefit is not always realized. In this paper, we provide one potential explanation for this discrepancy and suggest potential remedies. Using a queueing game between two EDs that aim to minimize their own waiting time, we find that decentralized decisions regarding diversion explain the lack of pooling benefits. Specifically, we find the existence of a defensive equilibrium, wherein each ED does not accept diverted ambulances from the other ED. This defensiveness results in a depooling of the network and, subsequently, in delays that are significantly higher than when a social planner coordinates diversion. The social optimum is itself difficult to characterize analytically and has limited practical appeal because it depends on problem parameters such as arrival rates and length of stay. Instead, we identify an alternative solution that does not require the exact knowledge of the parameters and may be used by the EMS agencies to coordinate diversion decisions when defensive diversion is present. We show that this solution is approximately optimal for the social planner's problem. Moreover, it is Pareto improving over the defensive equilibrium whereas the social optimum, in general, might not be. DEWEY : 658 ISSN : 0025-1909 En ligne : http://mansci.journal.informs.org/content/57/7.toc [article] Centralized vs. decentralized ambulance diversion : A network perspective [texte imprimé] / Sarang Deo, Auteur ; Gurvich Itai, Auteur . - 2011 . - pp. 1300-1319. Management Langues : Anglais (eng) in Management science > Vol. 57 N° 7 (Juillet 2011) . - pp. 1300-1319 Mots-clés : Emergency  department  Ambulance  diversion  Game  theory  Queueing  networks Index. décimale : 658 Organisation des entreprises. Techniques du commerce Résumé : One of the most important operational challenges faced by emergency departments (EDs) in the United States is patient overcrowding. In periods of overcrowding, an ED can request the emergency medical services (EMS) agency to divert incoming ambulances to neighboring hospitals, a phenomenon known as “ambulance diversion.” The EMS agency may accept this request provided that at least one of the neighboring EDs is not on diversion. From an operations perspective, properly executed ambulance diversion should result in resource pooling and reduce the overcrowding and delays in a network of EDs. Recent evidence indicates, however, that this potential benefit is not always realized. In this paper, we provide one potential explanation for this discrepancy and suggest potential remedies. Using a queueing game between two EDs that aim to minimize their own waiting time, we find that decentralized decisions regarding diversion explain the lack of pooling benefits. Specifically, we find the existence of a defensive equilibrium, wherein each ED does not accept diverted ambulances from the other ED. This defensiveness results in a depooling of the network and, subsequently, in delays that are significantly higher than when a social planner coordinates diversion. The social optimum is itself difficult to characterize analytically and has limited practical appeal because it depends on problem parameters such as arrival rates and length of stay. Instead, we identify an alternative solution that does not require the exact knowledge of the parameters and may be used by the EMS agencies to coordinate diversion decisions when defensive diversion is present. We show that this solution is approximately optimal for the social planner's problem. Moreover, it is Pareto improving over the defensive equilibrium whereas the social optimum, in general, might not be. DEWEY : 658 ISSN : 0025-1909 En ligne : http://mansci.journal.informs.org/content/57/7.toc

Staffing call centers with uncertain demand forecasts / Gurvich Itai in Management science, Vol. 56 N° 7 (Juillet 2010) 

Public ISBD [article]  in Management science > Vol. 56 N° 7 (Juillet 2010) . - pp. 1093-1115 Titre : Staffing call centers with uncertain demand forecasts : A chance-constrained optimization approach Type de document : texte imprimé Auteurs : Gurvich Itai, Auteur ; James Luedtke, Auteur ; Tolga Tezcan, Auteur Année de publication : 2010 Article en page(s) : pp. 1093-1115 Note générale : Management Langues : Anglais (eng) Mots-clés : Call  centers  Chance-constrained  optimization  Queueing Index. décimale : 658 Organisation des entreprises. Techniques du commerce Résumé : We consider the problem of staffing call centers with multiple customer classes and agent types operating under quality-of-service (QoS) constraints and demand rate uncertainty. We introduce a formulation of the staffing problem that requires that the QoS constraints are met with high probability with respect to the uncertainty in the demand rate. We contrast this chance-constrained formulation with the average-performance constraints that have been used so far in the literature. We then propose a two-step solution for the staffing problem under chance constraints. In the first step, we introduce a random static planning problem (RSPP) and discuss how it can be solved using two different methods. The RSPP provides us with a first-order (or fluid) approximation for the true optimal staffing levels and a staffing frontier. In the second step, we solve a finite number of staffing problems with known arrival rates—the arrival rates on the optimal staffing frontier. Hence, our formulation and solution approach has the important property that it translates the problem with uncertain demand rates to one with known arrival rates. The output of our procedure is a solution that is feasible with respect to the chance constraint and nearly optimal for large call centers. DEWEY : 658 ISSN : 0025-1909 En ligne : http://mansci.journal.informs.org/content/56/7.toc [article] Staffing call centers with uncertain demand forecasts : A chance-constrained optimization approach [texte imprimé] / Gurvich Itai, Auteur ; James Luedtke, Auteur ; Tolga Tezcan, Auteur . - 2010 . - pp. 1093-1115. Management Langues : Anglais (eng) in Management science > Vol. 56 N° 7 (Juillet 2010) . - pp. 1093-1115 Mots-clés : Call  centers  Chance-constrained  optimization  Queueing Index. décimale : 658 Organisation des entreprises. Techniques du commerce Résumé : We consider the problem of staffing call centers with multiple customer classes and agent types operating under quality-of-service (QoS) constraints and demand rate uncertainty. We introduce a formulation of the staffing problem that requires that the QoS constraints are met with high probability with respect to the uncertainty in the demand rate. We contrast this chance-constrained formulation with the average-performance constraints that have been used so far in the literature. We then propose a two-step solution for the staffing problem under chance constraints. In the first step, we introduce a random static planning problem (RSPP) and discuss how it can be solved using two different methods. The RSPP provides us with a first-order (or fluid) approximation for the true optimal staffing levels and a staffing frontier. In the second step, we solve a finite number of staffing problems with known arrival rates—the arrival rates on the optimal staffing frontier. Hence, our formulation and solution approach has the important property that it translates the problem with uncertain demand rates to one with known arrival rates. The output of our procedure is a solution that is feasible with respect to the chance constraint and nearly optimal for large call centers. DEWEY : 658 ISSN : 0025-1909 En ligne : http://mansci.journal.informs.org/content/56/7.toc