Optimal Workflow Decisions for Investigators in Systems with Interruptions

References

• Ahn H, Righter R. Dynamic load balancing with flexible workers. Adv. Appl. Probab. (2006) 38(3):621–642Crossref, Google Scholar
• Ahn H, Duenyas I, Lewis ME. Optimal control of a two-stage tandem queuing system with flexible servers. Probab. Engrg. Informational Sci. (2002) 16(4):453–469Google Scholar
• Ahn H, Duenyas I, Zhang RQ. Optimal stochastic scheduling of a two-stage tandem queue with parallel servers. Adv. Appl. Probab. (1999) 31(4):1095–1117Crossref, Google Scholar
• Altman E, Feinberg EA, Shwartz A. Applications of Markov decision processes in communication networks: A survey. Handbook of Markov Decision Processes (2002) (Kluwer, Dordrecht, The Netherlands) Crossref, Google Scholar
• Andradottir S, Ayhan H. Throughput maximization for tandem lines with two stations and flexible servers. Oper. Res. (2005) 53(3):516–531Link, Google Scholar
• Andradottir S, Ayhan H, Down DG. Server assignment policies for maximizing the steady-state throughput of finite queueing systems. Management Sci. (2001) 47(10):1421–1439Link, Google Scholar
• Andradóttir S, Ayhan H, Down DG. Maximizing the throughput of tandem lines with flexible failure-prone servers and finite buffers.. Probab. Engrg. Informational Sci. (2008) 22(2):191–211Google Scholar
• Argon NT, Ziya S. Priority assignment under imperfect information on customer type identities. Manufacturing Service Oper. Management (2009) 11(4):674–693Link, Google Scholar
• Arumugam R, Mayorga M, Taaffe K. Inventory based allocation policies for flexible servers in serial systems. Ann. Oper. Res. (2009) 172(1):1–23Crossref, Google Scholar
• Bartholdi JJ, Eisenstein DD. A production line that balances itself. Oper. Res. (1996) 44(1):21–34Link, Google Scholar
• Bell SL, Williams RJ. Dynamic scheduling of a system with two parallel servers in heavy traffic with resource pooling: Asymptotic optimality of a threshold policy. Ann. Appl. Probab. (2001) 11(3):608–649Crossref, Google Scholar
• Bell SL, Williams RJ. Dynamic scheduling of a parallel server system in heavy traffic with complete resource pooling: Asymptotic optimality of a threshold policy. Electron. J. Probab. (2005) 10(33):1044–1115Crossref, Google Scholar
• Besbes O, Maglaras C. Revenue optimization for a make-to-order queue in an uncertain market environment. Oper. Res. (2009) 57(6):1438–1450Link, Google Scholar
• Bramson M. State space collapse with application to heavy traffic limits for multiclass queueing networks. Queueing Systems: Theory Appl. (1998) 30(1–2):89–148Crossref, Google Scholar
• Bramson M, Dai JG. Heavy traffic limits for some queueing networks. Ann. Appl. Probab. (2001) 11(1):49–90Crossref, Google Scholar
• Chevalier PB, Wein LM. Scheduling networks of queues: Heavy traffic analysis of a multistation closed network. Oper. Res. (1993) 41(4):743–758Link, Google Scholar
• Chisholm CD, Collison EK, Nelson DR, Cordell WH. Emergency department workplace interruptions: Are emergency physicians “interrupt-driven” and “multitasking”? Acad. Emergency Medicine (2000) 7(11):1239–1243Crossref, Google Scholar
• Dai JG, Tezcan T. Optimal control of parallel server systems with many servers in heavy traffic. Queueing Systems (2008) 59(2):95–134Crossref, Google Scholar
• Dai JG, Tezcan T. State space collapse in many server diffusion limits of parallel server systems. Math. Oper. Res. (2011) 36(2):271–320Link, Google Scholar
• Dai JG, Wuqin L. Asymptotic optimality of maximum pressure policies in stochastic processing networks. Ann. Appl. Probab. (2008) 18(6):2239–2299Crossref, Google Scholar
• Dobson G, Sainathan A. On the impact of analyzing customer information and prioritizing in a service system. Decision Support Systems (2011) 51(4):875–883Crossref, Google Scholar
• Duenyas I, Gupta D, Olsen TL. Control of a single-server tandem queueing system with setups. Oper. Res. (1998) 46(2):218–230Link, Google Scholar
• Gans N, Koole G, Mandelbaum A. Telephone call centers: Tutorial, review, and research prospects. Manufacturing Service Oper. Management (2003) 5(2):79–141Link, Google Scholar
• Gel ES, Hopp WJ, Van Oyen MP. Factors affecting opportunity of worksharing as a dynamic line balancing mechanism. IIE Trans. (2002) 34(10):847–863Crossref, Google Scholar
• Gilland WG. Effective sequencing rules for closed manufacturing networks. Oper. Res. (2001) 49(5):759–770Link, Google Scholar
• Gurvich I, Whitt W. Scheduling flexible servers with convex delay costs in many-server service systems. Manufacturing Service Oper. Management (2009) 11(2):237–253Link, Google Scholar
• Harrison JM, Wein LM. Scheduling networks of queues: Heavy traffic analysis of a two-station closed network. Oper. Res. (1990) 38(6):1052–1064Link, Google Scholar
• Hu B, Benjaafar S. Partitioning of servers in queueing systems during rush hour. Manufacturing Service Oper. Management (2009) 11(3):416–428Link, Google Scholar
• Iravani SMR, Posner MJM, Buzacott JA. A two-stage tandem queue attended by a moving server with holding and switching costs. Queueing Systems: Theory Appl. (1997) 26(3–4):203–228Crossref, Google Scholar
• Kaufman D, Ahn H, Lewis M. On the introduction of an agile, temporary workforce into a tandem queueing system. Queueing Systems: Theory Appl. (2005) 51(1):135–171Crossref, Google Scholar
• Kirkizlar HE. Performance improvements through flexible workforce. (2008) . Unpublished doctoral dissertation, Georgia Institute of Technology, AtlantaGoogle Scholar
• Kirkizlar HE, Andradottir S, Ayhan H. Flexible servers in understaffed tandem lines. Production Oper. Management (2012) 21(4):761–777Crossref, Google Scholar
• Kumar S. Two-server closed networks in heavy traffic: Diffusion limits and asymptotic optimality. Ann. Appl. Probab. (2000) 10(3):930–961Crossref, Google Scholar
• Mandelbaum A, Stolyar AL. Scheduling flexible servers with convex delay costs: Heavy-traffic optimality of the generalized cμ-rule. Oper. Res. (2004) 52(6):836–855Link, Google Scholar
• McClain JO, Thomas LJ, Sox C. “On-the-fly” line balancing with very little WIP. Internat. J. Production Econom. (1992) 27(3):283–289Crossref, Google Scholar
• Oredsson S, Jonsson H, Rognes J, Lind L, Göransson KE, Ehrenberg A, Asplund K, Castrén M, Farrohknia N. A systematic review of triage-related interventions to improve patient flow in emergency departments. Scandinavian J. Trauma, Resuscitation and Emergency Medicine (2011) 19(43). http://www.sjtrem.com/content/19/1/43Google Scholar
• Rosberg Z, Varaiya P, Walrand J. Optimal control of service in tandem queues. IEEE Trans. Automatic Control (1982) 27(3):600–609Crossref, Google Scholar
• Saghafian S, Hopp WJ, Van Oyen MP, Desmond JS, Kronick SL. Complexity-based triage: A tool for improving patient safety and operational efficiency. (2012) . Ross School of Business Paper 1161, University of Michigan, Ann ArborGoogle Scholar
• Speier C, Valacich J. The influence of task interruption on individual decision making: An information overload perspective. Decision Sci. (1999) 30(2):337–360Crossref, Google Scholar
• Van Oyen MP, Hopp WJ. Agile workforce evaluation: A framework for cross-training and coordination. IIE Trans. (2004) 36(10):919–940Crossref, Google Scholar
• Westbrook JI, Woods A, Rob MI, Dunsmuir WTM, Day RO. Association of interruptions with an increased risk and severity of medication administration errors. Arch. Internal Medicine (2010) 170(8):683–690Crossref, Google Scholar
• Whitt W. Partitioning customers into service groups. Management Sci. (1999) 45(11):1579–1592Link, Google Scholar
• Wu C, Down DG, Lewis ME. Heuristics for allocation of reconfigurable resources in a serial line with reliability considerations. IIE Trans. (2008) 40(6):595–611Crossref, Google Scholar
• Wu C, Lewis ME, Veatch M. Dynamic allocation of reconfigurable resources in a two-stage tandem queueing system with reliability considerations. IEEE Trans. Automatic Control (2006) 51(2):309–314Crossref, Google Scholar
• Zavadlav E, McClain JO, Thomas LJ. Self-buffering, self-balancing, self-flushing production lines. Management Sci. (1996) 42(8):1151–1164Link, Google Scholar