The pointwise stationary approximation for M1/M1/s
Management Science
Strong approximations for Markovian service networks
Queueing Systems: Theory and Applications
Heavy traffic resource pooling in parallel-server systems
Queueing Systems: Theory and Applications
Queueing Systems: Theory and Applications
Commissioned Paper: Telephone Call Centers: Tutorial, Review, and Research Prospects
Manufacturing & Service Operations Management
A Method for Staffing Large Call Centers Based on Stochastic Fluid Models
Manufacturing & Service Operations Management
Fluid Models for Multiserver Queues with Abandonments
Operations Research
Optimal capacity planning in stochastic loss networks with time-varying workloads
Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Dynamic routing of customers with general delay costs in a multiserver queuing system
Probability in the Engineering and Informational Sciences
Pointwise Stationary Fluid Models for Stochastic Processing Networks
Manufacturing & Service Operations Management
Mathematics of Operations Research
On a Data-Driven Method for Staffing Large Call Centers
Operations Research
Service Interruptions in Large-Scale Service Systems
Management Science
Bid-Price Controls for Network Revenue Management: Martingale Characterization of Optimal Bid Prices
Mathematics of Operations Research
NET-COOP'07 Proceedings of the 1st EuroFGI international conference on Network control and optimization
Control of systems with flexible multi-server pools: a shadow routing approach
Queueing Systems: Theory and Applications
The cμ/θ Rule for Many-Server Queues with Abandonment
Operations Research
Shadow-Routing Based Control of Flexible Multiserver Pools in Overload
Operations Research
Robust Design and Control of Call Centers with Flexible Interactive Voice Response Systems
Manufacturing & Service Operations Management
Dynamic Pricing with Financial Milestones: Feedback-Form Policies
Management Science
A Fluid Limit for an Overloaded X Model via a Stochastic Averaging Principle
Mathematics of Operations Research
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Motivated by applications in telephone call centers, we consider a service system model with m customer classes and r server pools. The model is one with doubly stochastic arrivals, which means that the m-vector 驴 of instantaneous arrival rates is allowed to vary both temporally and stochastically. Two levels of dynamic control are considered: customers may be either blocked or accepted at the time of their arrival, and then accepted customers of each class must be routed, either immediately upon acceptance or after some period of waiting, to a server pool that is qualified to handle that class. Customers who are made to wait before commencement of their service are liable to defect. The objective is to minimize the expected sum of blocking costs, waiting costs and defection costs over a fixed and finite planning horizon. We consider an asymptotic parameter regime in which (i) the arrival rates, service rates and defection rates are uniformly accelerated by a large factor 驴, then (ii) arrival rates are increased by an additional factor g(驴), and the number of servers in each pool is increased by g(驴) as well. This produces a separation of time scales, justifying a pointwise stationary stochastic fluid approximation for our original system model. In the stochastic fluid approximation, optimal admission control and routing decisions are determined by a simple linear program that uses the current arrival rate vector 驴 as data. We explain how to implement the fluid model's optimal control policy in our original service system context, and prove that the proposed implementation is asymptotically optimal in the first-order sense.