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We consider a class of queueing systems that consist of server pools in parallel and multiple customer classes. Customer service times are assumed to be exponentially distributed. We study the asymptotic behavior of these queueing systems in a heavy traffic regime that is known as the Halfin-Whitt many-server asymptotic regime. Our main contribution is a(More)
We consider a class of parallel server systems that are known as N-systems. In an N-system, there are two customer classes that are catered by servers in two pools. Servers in one of the pools are cross-trained and can serve customers from both classes whereas all the servers in the other pool can only serve one of the customer classes. A customer reneges(More)
A general model with multiple input flows (classes) and several flexible multi-server pools is considered. We propose a robust, generic scheme for routing new arrivals, which optimally balances server pools' loads, without the knowledge of the flow input rates and without solving any optimization problem. The scheme is based on Shadow routing in a virtual(More)
We consider a parallel server system that consists of several customer classes and server pools in parallel. We propose a simple robust control policy to minimize the total linear holding and reneging costs. We show that this policy is as-ymptotically optimal under the many-server heavy traffic regime for parallel server systems when the service times are(More)
W e consider the problem of staffing call centers with multiple customer classes and agent types operating under quality-of-service (QoS) constraints and demand rate uncertainty. We introduce a formulation of the staffing problem that requires that the QoS constraints are met with high probability with respect to the uncertainty in the demand rate. We(More)
We consider a general parallel server system model with multiple customer classes and several flexible multi-server pools, in the many-server asymptotic regime where the input rates and server pool sizes are scaled up linearly to infinity. Service of a customer brings a constant reward, which depends on its class. The objective is to maximize the long-run(More)
We model a system which consists of a stream of customers processed through three steps by two resources. The first resource, an investigator, handles the first step, in which she collects information from the customer and decides what work will be done in the second step by the second resource, the back office. In the third step the investigator returns to(More)