Analysis of a discrete-time queueing system with an NT-policy

In this paper, we analyse a discrete-time single-server queue operating under the NT-policy, which aims at clustering the service of customers in order to reduce the number of server activations and deactivations. Starting from an empty queue, the service of arriving customers is postponed until either of two thresholds is reached. Specifically, exhaustive service of customers is initiated only if either N customers have accumulated (space threshold) or if more than slots have passed since the arrival of the first customer. This way, the queue cycles between three states, i.e. an empty phase, an accumulating phase and a serving phase. A Bernoulli arrival process and deterministic service times are assumed. We derive the steady-state probabilities of the system's state as well as the distributions of the phase sojourn times and the customer delay. For the latter, we condition on the phase during the customer's arrival slot. The influence of the model parameters on the results is discussed by means of a numerical example

A queueing-theoretic analysis of the threshold-based exhaustive data-backup scheduling policy

We analyse the threshold-based exhaustive data backup scheduling mechanism by means of a queueing-theoretic approach. Data packets that have not yet been backed up are modelled by customers waiting for service (back-up). We obtain the probability generating function of the system content (backlog size) at random slot boundaries in steady state

Preparation of chemotherapy drugs: planning policy for reduced waiting times

This study investigates the impact of pharmacy policies on patient waiting time in the Chemotherapy Day Unit of the Netherland Cancer Institute - Antoni van Leeuwenhoek hospital (NKI-AVL). The project evaluated whether a reduction in waiting time resulting from medication orders being prepared in advance of patient appointments was justified, given that medications prepared in advance risked being wasted if patients arrived too sick for treatment. Within this context, we derive explicit expressions to approximate patient waiting times and wastage costs allowing management to see the tradeoff between these two metrics for different policies. Using a case study and a simulation model, the approximations are evaluated. The explicit expressions allow the analysis to be easily repeated when medication costs change or when new medications/protocols are introduced. In the same vein, other hospitals with different patient case mixes can easily complete the analysis in their setting. Finally, the outcome from this study resulted in a new policy at the cancer centre which is expected to decrease the waiting time by half while only increasing pharmacy’s costs by 1-2%