Erlang-R: A Time-Varying Queue with Reentrant Customers, in Support of Healthcare Staffing

References

• Armony M, Israelit S, Mandelbaum A, Marmor YN, Tseytlin Y, Yom-Tov GB (2011) Patient flow in hospitals: A data-based queueing-science perspective. Working paper, Technion–Israel Institute of Technology, Technion City, Haifa. http://iew3.technion.ac.il/serveng/References/references.Google Scholar
• Borst S, Mandelbaum A, Reiman M (2004) Dimensioning large call centers. Oper. Res. 52(1):17–34.Link, Google Scholar
• Chan CW, Yom-Tov GB, Escobar G (2014) When to use speedup: An examination of service systems with returns. Oper. Res. 62(2):462–482.Link, Google Scholar
• Cohen I, Mandelbaum A, Zychlinski N (2014) Minimizing mortality in a mass casualty event: Fluid networks in support of modeling and staffing. IIE Trans. 46(7):728–741.Crossref, Google Scholar
• Eick SG, Massey WA, Whitt W (1993a) Mt/G/∞ queues with sinusoidal arrival rates. Management Sci. 39(2):241–252.Link, Google Scholar
• Eick SG, Massey WA, Whitt W (1993b) The physics of the Mt/G/∞ queue. Oper. Res. 41(4):731–742.Link, Google Scholar
• Falin GI, Templeton JGC (1997) Retrial Queues (Chapman & Hall, London).Crossref, Google Scholar
• Feldman Z, Mandelbaum A, Massey WA, Whitt W (2008) Staffing of time-varying queues to achieve time-stable performance. Management Sci. 54(2):324–338.Link, Google Scholar
• Gans N, Koole G, Mandelbaum A (2003) Telephone call centers: A tutorial and literature review. Manufacturing Service Oper. Management 5(2):79–141.Link, Google Scholar
• Green L, Kolesar PJ, Soares J (2001) Improving the SIPP approach for staffing service systems that have cyclic demands. Oper. Res. 49(4):549–564.Link, Google Scholar
• Green L, Kolesar PJ, Whitt W (2007) Coping with time-varying demand when setting staffing requirements for a service system. Production Oper. Management 16(1):13–39.Crossref, Google Scholar
• Green L, Soares J, Giglio JF, Green RA (2006) Using queuing theory to increase the effectiveness of emergency department provider staffing. Academic Emergency Medicine 13(1):61–68.Crossref, Google Scholar
• Halfin S, Whitt W (1981) Heavy-traffic limits for queues with many exponential servers. Oper. Res. 29(3):567–588.Link, Google Scholar
• Huang J, Carmeli B, Mandelbaum A (2012) Control of patient flow in emergency departments, or multiclass queues with deadlines and feedback. Working paper, Technion–Israel Institute of Technology, Technion City, Haifa.Google Scholar
• Israel Ministry of Health (2006) Financial report for years 2000–2005. Report, Israel Ministry of Health, Jerusalem. http://www.health.gov.il/publicationsFiles/finance2005.pdf.Google Scholar
• Jacobson EU, Argon NT, Ziya S (2012) Priority assignment in emergency response. Oper. Res. 60(4):813–832.Link, Google Scholar
• Janssen AJEM, van Leeuwaarden JSH, Zwart B (2011) Refining square-root safety staffing by expanding Erlang C. Oper. Res. 59(6):1512–1522.Link, Google Scholar
• Jennings OB, de Véricourt F (2011) Nurse staffing in medical units: A queueing perspective. Oper. Res. 59(6):1320–1331.Link, Google Scholar
• Jennings OB, Mandelbaum A, Massey WA, Whitt W (1996) Server staffing to meet time-varying demand. Management Sci. 42(10):1383–1394.Link, Google Scholar
• Kaplan EL, Meier P (1958) Nonparametric estimation from incomplete observations. J. Amer. Statist. Assoc. 53(282):457–481.Crossref, Google Scholar
• Khudyakov P, Gorfine M, Feigin P (2010) Test for equality of baseline hazard functions for correlated survival data using frailty models. Working paper, Technion–Israel Institute of Technology, Technion City, Haifa.Google Scholar
• Lahiri A, Seidmann A (2009) Analyzing the differential impact of radiology information systems across radiology modalities. J. Amer. College of Radiology 6(10):522–526.Crossref, Google Scholar
• Maman S (2009) Uncertainty in the demand for service: The case of call centers and emergency departments. Master's thesis, Technion–Israel Institute of Technology, Technion City, Haifa.Google Scholar
• Mandelbaum A, Massey W, Reiman M (1998) Strong approximations for Markovian service networks. Queueing Systems 30(1–2):149–201.Crossref, Google Scholar
• Mandelbaum A, Massey WA, Reiman M, Rider B (1999) Time varying multiserver queues with abandonment and retrials. Key P, Smith D, eds. Teletraffic Engineering in a Competitive World (Elsevier, Amsterdam), 355–364.Google Scholar
• Mandelbaum A, Massey WA, Reiman M, Stolyar A, Rider B (2002) Queue lengths and waiting times for multiserver queues with abandonment and retrials. Telecomm. Systems 21(2–4):149–171.Crossref, Google Scholar
• Marmor Y, Sinreich DA (2005) Emergency department operations: The basis for developing a simulation tool. IIE Trans. 37(3):233–245.Crossref, Google Scholar
• Massey WA, Whitt W (1993) Networks of infinite-server queues with nonstationary Poisson input. Queueing Systems 13(1):183–250.Crossref, Google Scholar
• Massey W, Whitt W (1994) An analysis of the modified offered-load approximation for the nonstationary Erlang loss model. Ann. Appl. Probab. 4(4):1145–1160.Crossref, Google Scholar
• Whitt W (2007) What you should know about queueing models to set staffing requirements in service systems. Naval Res. Logist. 55(5):476–484.Crossref, Google Scholar
• Whitt W (2013) Offered load analysis for staffing. Manufacturing Service Oper. Management 15(2):166–169.Link, Google Scholar
• Yom-Tov G (2010) Queues in hospitals: Queueing networks with reentering customers in the QED regime. Ph.D. thesis, Technion–Israel Institute of Technology, Technion City, Haifa.Google Scholar
• Zeltyn S, Marmor YN, Mandelbaum A, Carmeli B, Greenshpan O, Mesika Y, Wasserkrug Set al. (2011) Simulation-based models of emergency departments: Operational, tactical, and strategic staffing. ACM Trans. Modeling Comput. Simulation (TOMACS) 21(4):Article 24.Crossref, Google Scholar
• Zhan D, Ward AR (2014) Threshold routing to trade off waiting and call resolution in call centers. Manufacturing Service Oper. Management 16(2):220–237.Link, Google Scholar