Pengfei Guo

Strategic behavior and social optimization in partially-observable Markovian vacation queues

Abstract We study customers’ strategic behavior and social optimization in vacation queues with N -policy under two partial-information scenarios. In scenarioxa01, only the server’s status is observable. We find that avoid-the-crowd/follow-the-crowd behavior exists when the server is busy/idle. In scenarioxa02, only the queue length is observable. The customers’ equilibrium threshold strategy is the same as that in a fully observable system; whereas, the optimal control policy in a fully observable case is sometimes, but not always, implementable in scenarioxa02.

A fair staff allocation rule for the capacity pooling of multiple call centers

We construct a cooperative sta¢ ng game to investigate how to fairly allocate the reduced number of stas among multiple call centers that pool (centralize) their capacities. We show that this game is essential and submodular, and thereby, convex with a non-empty core. We also propose a neat Shapley value-characterized sta¤-allocation rule, which exists in the core of the game.