Routing and Staffing in Large-Scale Service Systems: The Case of Homogeneous Impatient Customers and Heterogeneous Servers

Motivated by call centers, we study large-scale service systems with homogeneous impatient customers and heterogeneous servers; the servers differ with respect to their speed of service. For this model, we propose staffing and routing rules that are jointly asymptotically optimal in the heavy-traffic many-server QED, ED, and ED + QED regimes, respectively. For the QED regime, our proposed routing rule is FSF, that assigns customers to the fastest server available first. In the ED and ED + QED regimes, all work-conserving policies perform (asymptotically) equally well. In all these regimes, the form of the asymptotically optimal staffing is consistent with the asymptotically optimal staffing in the same regimes in the single-pool case, respectively. In particular, the total service capacity is (asymptotically) equal to a term that is proportional to the arrival rate plus, possibly, a term that is proportional to the square-root of the arrival rate, with both terms being regime dependent. Our specific proposed approximation for the optimal staffing vector is obtained via a straightforward solution to a deterministic optimization problem subject to a linear feasible region.

[1]  Constantinos Maglaras,et al.  Diffusion Approximations for a Multiclass Markovian Service System with "Guaranteed" and "Best-Effort" Service Levels , 2004, Math. Oper. Res..

[2]  Avishai Mandelbaum,et al.  Simplified Control Problems for Multiclass Many-Server Queueing Systems , 2009, Math. Oper. Res..

[3]  Amy R. Ward,et al.  Fair Dynamic Routing in Large-Scale Heterogeneous-Server Systems , 2010, Oper. Res..

[4]  Tolga Tezcan,et al.  State Space Collapse in Many-Server Diffusion Limits of Parallel Server Systems , 2011, Math. Oper. Res..

[5]  Avishai Mandelbaum,et al.  Empirical analysis of a call center , 2000 .

[6]  Constantinos Maglaras,et al.  Pricing and Design of Differentiated Services: Approximate Analysis and Structural Insights , 2005, Oper. Res..

[7]  J. Michael Harrison,et al.  Dynamic Routing and Admission Control in High-Volume Service Systems: Asymptotic Analysis via Multi-Scale Fluid Limits , 2005, Queueing Syst. Theory Appl..

[8]  Rami Atar,et al.  A blind policy for equalizing cumulative idleness , 2011, Queueing Syst. Theory Appl..

[9]  Fabricio Bandeira Cabral,et al.  The Slow Server Problem for Uninformed Customers , 2005, Queueing Syst. Theory Appl..

[10]  S. Ethier,et al.  Markov Processes: Characterization and Convergence , 2005 .

[11]  Ward Whitt,et al.  Service-Level Differentiation in Many-Server Service Systems : A Solution Based on Fixed-Queue-Ratio Routing , 2007 .

[12]  Tolga Tezcan,et al.  Optimal control of parallel server systems with many servers in heavy traffic , 2008, Queueing Syst. Theory Appl..

[13]  Opher Baron,et al.  Staffing to Maximize Profit for Call Centers with Alternate Service-Level Agreements , 2009, Oper. Res..

[14]  R. Stockbridge A martingale approach to the slow server problem , 1991 .

[15]  Itay Gurvich,et al.  Service-Level Differentiation in Call Centers with Fully Flexible Servers , 2008, Manag. Sci..

[16]  Ward Whitt Two fluid approximations for multi-server queues with abandonments , 2005, Oper. Res. Lett..

[17]  Ward Whitt,et al.  Heavy-Traffic Limits for Queues with Many Exponential Servers , 1981, Oper. Res..

[18]  Ward Whitt,et al.  Scheduling Flexible Servers with Convex Delay Costs in Many-Server Service Systems , 2009, Manuf. Serv. Oper. Manag..

[19]  Ward Whitt,et al.  Fluid Models for Multiserver Queues with Abandonments , 2006, Oper. Res..

[20]  Ward Whitt,et al.  A multi-class fluid model for a contact center with skill-based routing , 2006 .

[21]  Amy R. Ward,et al.  Critical Thresholds for Dynamic Routing in Queueing Networks , 2002, Queueing Syst. Theory Appl..

[22]  Sem C. Borst,et al.  Dimensioning Large Call Centers , 2000, Oper. Res..

[23]  Ward Whitt,et al.  Service-Level Differentiation in Many-Server Service Systems via Queue-Ratio Routing , 2010, Oper. Res..

[24]  M. Rubinovitch The Slow Server Problem , 1983 .

[25]  Tolga Tezcan,et al.  Asymptotically optimal control of many-server heterogeneous service systems with $H_{2}^{*}$ service times , 2012, Queueing Syst. Theory Appl..

[26]  Zeynep Akşin,et al.  The Modern Call Center: A Multi‐Disciplinary Perspective on Operations Management Research , 2007 .

[27]  Avishai Mandelbaum,et al.  Service times in call centers: Agent heterogeneity and learning with some operational consequences , 2010 .

[28]  Rami Atar,et al.  Efficient Routing in Heavy Traffic Under Partial Sampling of Service Times , 2008, Math. Oper. Res..

[29]  Ward Whitt,et al.  Staffing a Call Center with Uncertain Arrival Rate and Absenteeism , 2006 .

[30]  Avishai Mandelbaum,et al.  Designing a Call Center with Impatient Customers , 2002, Manuf. Serv. Oper. Manag..

[31]  Ward Whitt,et al.  Queue-and-Idleness-Ratio Controls in Many-Server Service Systems , 2009, Math. Oper. Res..

[32]  N. Shimkin,et al.  The c / Rule for Many-Server Queues with Abandonment , 2009 .

[33]  Ashok K. Agrawala,et al.  Control of a Heterogeneous Two-Server Exponential Queueing System , 1983, IEEE Transactions on Software Engineering.

[34]  Constantinos Maglaras,et al.  Pricing and Capacity Sizing for Systems with Shared Resources: Approximate Solutions and Scaling Relations , 2003, Manag. Sci..

[35]  Avishai Mandelbaum,et al.  Telephone Call Centers: Tutorial, Review, and Research Prospects , 2003, Manuf. Serv. Oper. Manag..

[36]  J. Michael Harrison,et al.  Design and Control of a Large Call Center: Asymptotic Analysis of an LP-Based Method , 2006, Oper. Res..

[37]  Nahum Shimkin,et al.  The cµ/theta Rule for Many-Server Queues with Abandonment , 2010, Oper. Res..

[38]  Ward Whitt,et al.  Efficiency-Driven Heavy-Traffic Approximations for Many-Server Queues with Abandonments , 2004, Manag. Sci..

[39]  Mor Armony,et al.  Dynamic Routing in Large-Scale Service Systems with Heterogeneous Servers , 2005, Queueing Syst. Theory Appl..

[40]  Avishai Mandelbaum,et al.  Staffing Many-Server Queues with Impatient Customers: Constraint Satisfaction in Call Centers , 2009, Oper. Res..

[41]  Tolga Tezcan,et al.  Dynamic Control of N-Systems with Many Servers: Asymptotic Optimality of a Static Priority Policy in Heavy Traffic , 2010, Oper. Res..

[42]  V. V. Rykov,et al.  On the slow server problem , 2009 .

[43]  Francis de Véricourt,et al.  Managing Response Time in a Call-Routing Problem with Service Failure , 2005, Oper. Res..

[44]  P. R. Kumar,et al.  Optimal control of a queueing system with two heterogeneous servers , 1984 .

[45]  Francis de Véricourt,et al.  On the incomplete results for the heterogeneous server problem , 2006, Queueing Syst. Theory Appl..

[46]  MandelbaumAvishai,et al.  Scheduling Flexible Servers with Convex Delay Costs , 2004 .

[47]  Yulia Tseytlin,et al.  Queueing Systems with Heterogeneous Servers : Improving Patients ’ Flow in Hospitals M . Sc . Research Proposal , 2007 .

[48]  J. Michael Harrison,et al.  A Method for Staffing Large Call Centers Based on Stochastic Fluid Models , 2005, Manuf. Serv. Oper. Manag..

[49]  Rami Atar Central limit theorem for a many-server queue with random service rates. , 2008 .