Effects of pooling, specialization, and discretionary task completion on queueing performance

Pooling, unpooling/specialization, and discretionary task completion are typical operational strategies in queueing systems that arise in healthcare, call centers, and online sales. These strategies may have advantages and disadvantages in different operational environments. This paper uses the M=M=1 and M=M=2 queues to study the impact of pooling, specialization, and discretionary task completion on the average queue length. Closed-form solutions for the average M=M=2 queue length are derived. Computational examples illustrate how the average queue length changes with the strength of pooling, specialization, and discretionary task completion. Finally, several conjectures are made in the paper.