Amarjit Budhiraja

TL;DR: A flexible family of controls, called action time sharing (ATS) policies, associated with a given continuous stationary Markov control, is introduced and it is shown that the long-term average cost for such a control policy, for a broad range of one-stage cost functions, is the same as that for the associated stationaryMarkov policy.

TL;DR: In this paper, a scheduling control problem for a single-server multiclass queueing network in a changing environment is studied and an appropriate version of the classical C═-policy (the priority policy that favors classes with higher values of the product of holding cost and service rate) is asymptotically optimal for an in-time horizon discounted cost criterion.

TL;DR: This work proposes and analyzes a Monte- Carlo scheme based on an Euler type discretization of the reflected stochastic differential equation using a single sequence of time discretized steps which decrease to zero as time approaches infinity.

TL;DR: In this article, the robust Renyi bounds are used to obtain robust probabilistic estimates for queueing models at the large deviations (LD) scale, provided that the class is defined in terms of Renyi divergence with respect to a reference model and that estimates are available for the reference model.

TL;DR: The lower bounds established in this work show that the threshold control policies constructed in Budhiraja and Johnson (2017), which achieve the Hierarchical Greedy Ideal (HGI) performance in the heavy traffic limit, are in fact asymptotically optimal when certain monotonicity conditions on the cost function are satisfied.