Queueing Systems with Synergistic Servers

We consider tandem lines with finite buffers and flexible, heterogeneous servers who are synergistic in that they work more effectively in teams than on their own. Our objective is to determine how the servers should be assigned dynamically to tasks in order to maximize the long-run average throughput. In particular, we investigate when it is better to take advantage of synergy among servers, rather than exploiting the servers’ special skills, to achieve the best possible system throughput. For Markovian systems with two stations and two servers, we provide a complete characterization of the optimal policy and show that depending on how well the servers work together, the optimal policy either takes full advantage of servers’ special skills, or full advantage of server synergy (and hence there is no middle ground in this case). Moreover, for a class of Markovian systems, we provide sufficient conditions that guarantee that the optimal policy should take full advantage of server synergy at all times. Finally, we show that when there is no tradeoff between server synergy and servers’ special skills (because the servers are generalists who are equally skilled at all tasks), the optimal policy has servers working in teams of two or more at all times.