Shadow-routing based control of flexible multiserver pools in overload

Operations Research

Volumn 59, Issue 6, 2011, Pages 1427-1444

  Stolyar, Alexander L ^a   Tezcan, Tolga ^b  

^a LUCENT TECHNOLOGIES   (United States)

^b UNIVERSITY OF ROCHESTER   (United States)

Author keywords

Large flexible server pools; Many server asymptotics; Queueing networks; Revenue maximization; Routing and scheduling; Shadow routing

Indexed keywords

ASYMPTOTICS; FLEXIBLE SERVERS; REVENUE MAXIMIZATION; ROUTING AND SCHEDULING; SHADOW ROUTING;

CUSTOMER SATISFACTION; LAKES; OPTIMIZATION; QUEUEING NETWORKS;

SALES;

EID: 84855325146     PISSN: 0030364X     EISSN: 15265463     Source Type: Journal    
DOI: 10.1287/opre.1110.0960     Document Type: Article

References (32)

1. Aksin, Z., M. Armony, V. Mehrotra. 2007. The modern call-center: A multi-disciplinary perspective on operations management research. Production Oper. Management 16(6) 655-688.
2. Atar, R. 2005a. A diffusion model of scheduling control in queueing systems with many servers. Ann. Appl. Probab. 15(1B) 820-852. (Pubitemid 40306613)
3. Atar, R. 2005b. Scheduling control for queueing systems with many servers: Asymptotic optimality in heavy traffic. Ann. Appl. Probab. 15(4) 2606-2650. (Pubitemid 43106166)
4. Atar, R., C. Giat, N. Shimkin. 2010. The cμ/θ rule for many-server queues with abandonment. Oper. Res. 58(5) 1427-1439.
5. Atar, R., C. Giat, N. Shimkin. 2011. On the asymptotic optimality of the cμ/θ rule under ergodic cost. Queueing Systems 67(2) 127-144.
6. Atar, R., A. Mandelbaum, M. Reiman. 2004. Scheduling a multi-class queue with many exponential servers: Asymptotic optimality in heavy-traffic. Ann. Appl. Probab. 14(3) 1084-1134. (Pubitemid 41449212)
7. Bassamboo, A., R. S. Randhawa. 2010. On the accuracy of fluid models for capacity sizing in queueing systems with impatient customers. Oper. Res. 58(5) 1398-1413.
8. Bassamboo, A., A. Zeevi. 2009. On a data-driven method for staffing large call centers. Oper. Res. 57(3) 714-726.
9. Bassamboo, A., J. M. Harrison, A. Zeevi. 2006a. Design and control of a large call center: Asymptotic analysis of an LP-based method. Oper. Res. 54(3) 419-435. (Pubitemid 43838356)
10. Bassamboo, A., J. M. Harrison, A. Zeevi. 2006b. Dynamic routing and admission control in high-volume service systems: Asymptotic analysis via multi-scale fluid limits. Queueing Systems 51(3-4) 249-285. (Pubitemid 41813334)
11. Bassamboo, A., R. S. Randhawa, A. Zeevi. 2010. Capacity sizing under parameter uncertainty: Safety staffing principles revisited. Management Sci. 56(10) 1668-1686.
12. Dai, J. G., T. Tezcan. 2008. Dynamic control of parallel server systems in many server heavy traffic. Queueing Systems 59(2) 95-134.
13. Dai, J. G., S. He, T. Tezcan. 2010. Many-server diffusion limits for G/Ph/nCGI queues. Ann. Appl. Probab. 20(5) 1854-1890.
14. Gans, N., G. Koole, A. Mandelbaum. 2003. Telephone call centers: Tutorial, review and research prospects. Manufacturing Service Oper. Management 5(2) 79-141.
15. Gurvich, I., W. Whitt. 2007. Scheduling flexible servers with convex delay costs in many-server service systems. Manufacturing Service Oper. Management 11(2) 237-253.
16. Gurvich, I., W. Whitt. 2010. Service-level differentiation in manyserver service systems via queue-ratio routing. Oper. Res. 58(2) 316-328.
17. Harrison, J. M., A. Zeevi. 2004. Dynamic scheduling of a multiclass queue in the Halfin-Whitt heavy traffic regime. Oper. Res. 52(2) 243-257.
18. Kang, W., K. Ramanan. 2010. Fluid limits of many-server queues with reneging. Ann. Appl. Probab. 20(6) 2204-2260.
19. Kaspi, H., K. Ramanan. 2011. Law of large numbers limits for many server queues. Ann. Appl. Probab. 21(1) 33-114.
20. Mandelbaum, A., A. Stolyar. 2004. Scheduling flexible servers with convex delay costs: Heavy-traffic optimality of the generalized cμrule. Oper. Res. 52(6) 836-855. (Pubitemid 40122346)
21. Perry, O., W. Whitt. 2009. Responding to unexpected overloads in largescale service systems. Management Sci. 55(8) 1353-1367.
22. Perry, O., W. Whitt. 2011. A fluid approximation for service systems responding to unexpected overloads. Oper. Res. 59(5) 1159-1170.
23. Reed, J. 2009. The G/GI/N queue in the Halfin-Whitt regime. Ann. Appl. Probab. 19(6) 2211-2269.
24. Reed, J. 2010. The G/GI/N queue in the Halfin-Whitt regime II: Idle time system equations. Technical report, New York University.
25. Shaikhet, G. 2010. A fluid control problem in queueing networks with general service times. Technical report, Carnegie Mellon University, Pittsburgh.
26. Shakkottai, S., A. L. Stolyar. 2002. Scheduling for multiple flows sharing a time-varying channel: The exponential rule. Analytic Methods Appl. Probab. Amer. Math. Soc. Translations, Ser. 2 207 185-202.
27. Stolyar, A. L. 2005a. Maximizing queueing network utility subject to stability: Greedy primal-dual algorithm. Queueing Systems 50(4) 401-457. (Pubitemid 41312621)
28. Stolyar, A. L. 2005b. Optimal routing in output-queued flexible server systems. Probab. Engrg. Inform. Sci. 19(2) 141-189. (Pubitemid 40560661)
29. Stolyar, A. L., T. Tezcan. 2010. Control of systems with flexible multiserver pools: A shadow routing approach. Queueing Systems 66(1) 1-51.
30. Tezcan, T., J. G. Dai. 2010. Dynamic control of n-systems with many servers: Asymptotic optimality of a static priority policy in heavy traffic. Oper. Res. 58(1) 94-110.
31. Whitt, W. 2004. Efficiency-driven heavy-traffic approximations for many-server queues with abandonments. Management Sci. 50(10) 1449-1461.
32. Whitt, W. 2006. Fluid models for multiserver queues with abandonments. Oper. Res. 54(1) 37-54.