This article deals with the three classic policies for an M/G/1 queueing system (N, T, and D-policy). The optimum policies were compared in several precedent studies, but the comparison was performed employing different cost functions, so that the D-policy is superior to the N-policy when the cost function is based on the mean work-load, whilst the average queue length is used to show the superiority of the N-policy over the T-policy. In order to achieve a comparison of the three policies under...

We consider a Markov decision process for an ${M}^{X}/M/1$ queue that is controlled by batches of negative customers. More specifically, we derive conditions that imply threshold-type optimal policies, under either the total discounted cost criterion or the average cost criterion. The performance analysis of the model when it operates under a given threshold-type policy is also studied. We prove a stability condition and a complete stochastic comparison characterization for models operating under different...

We consider a Markov decision process for an queue that is
controlled by batches of negative customers. More specifically, we derive
conditions that imply threshold-type optimal policies, under either the
total discounted cost criterion or the average cost criterion. The
performance analysis of the model when it operates under a given
threshold-type policy is also studied. We prove a stability condition and a
complete stochastic comparison characterization for models operating under
different...

In this paper, information theoretic methodology for system modeling is applied to investigate the probability density function of the busy period in $M/G/1$ vacation models operating under the $N$-, $T$- and $D$-policies. The information about the density function is limited to a few mean value constraints (usually the first moments). By using the maximum entropy methodology one obtains the least biased probability density function satisfying the system’s constraints. The analysis of the three controllable...

In this paper, information theoretic methodology for
system modeling is applied to investigate the probability density function
of the busy period in vacation models operating under the -, - and
-policies. The information about the density function is limited to a few
mean value constraints (usually the first moments). By using the maximum
entropy methodology one obtains the least biased probability density
function satisfying the system's constraints. The analysis of the three
controllable queueing...

In this paper, we give a survey of the use of information theoretic techniques for the estimation of the main performance characteristics of the M/G/1 retrial queue. We focus on the limiting distribution of the system state, the length of a busy period and the waiting time. Numerical examples are given to illustrate the accuracy of the maximum entropy estimations when they are compared versus the classical solutions.

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