Maximizing Throughput in an M/G/1 Queue with Customer Abandonments

This paper studies the problem of identifying the optimal server assignment policy in single-server queues with customer abandonment.

We consider a system with Poisson arrivals and exponentially distributed patience times.

We show that when service times follow either an Erlang-$K$ or a hyperexponential distribution and the decision maker can observe the phase of a customer's service time, the Shortest Remaining Expected Processing Time (SREPT) policy maximizes the long-run average throughput, independent of the abandonment rate.