Scheduling Flexible Servers with Convex Delay Costs in Many-Server Service Systems

Abstract

In a recent paper we introduced the queue-and-idleness ratio (QIR) family of routing rules for many-server service systems with multiple customer classes and server pools. A newly available server serves the customer from the head of the queue of the class (from among those the server is eligible to serve) whose queue length most exceeds a specified proportion of the total queue length. Under fairly general conditions, QIR produces an important state-space collapse as the total arrival rate and the numbers of servers increase in a coordinated way. That state-space collapse was previously used to delicately balance service levels for the different customer classes. In this sequel, we show that a special version of QIR stochastically minimizes convex holding costs in a finite-horizon setting when the service rates are restricted to be pool dependent. Under additional regularity conditions, the special version of QIR reduces to a simple policy: linear costs produce a priority-type rule, in which the least-cost customers are given low priority. Strictly convex costs (plus other regularity conditions) produce a many-server analogue of the generalized-c\mu (Gc\mu ) rule, under which a newly available server selects a customer from the class experiencing the greatest marginal cost at that time.queues, many-server queues, heavy-traffic limits for queues, service systems, cost minimization in many-server queues, skill-based routing, generalized-c\mu rule, queue-and-idleness-ratio control