A finite capacity dynamic priority queuing model

TL;DR: This work provides an integrated framework to manage queue dynamically from both demand and supply perspectives and introduces intelligent dynamic patient prioritization strategies to manage the demand concurrently with dynamic resource adjustment policies to manage supply.

TL;DR: In this article, a priority polling system consisting of two queues attended by a single server is considered, where customers are served in groups, with the group service time distributed according to distribution with mean.

TL;DR: A single server queueing model with two parallel queues in which one is finite buffer and the other is infinite is considered, where ordinary customers are ordinary customers and the customers in the finite queue are priority customers.

TL;DR: An integrated framework that manages queues dynamically in the ED from both the demand and supply perspectives is presented, and a dynamic priority queue is found to be better than standard queuing solutions which are based on first-in-first-out (FIFO) or static priority queues.

TL;DR: The recursive computational schemes obtained here using the function-analytic methods recently introduced by M. F. Neuts can be used interactively in the design of such systems for arriving at desirable values of N and K.

TL;DR: In this paper, the authors consider a stochastic process X(t) (t ≧ 0) taking values in a countable state space, where a particle moves from state to state in such a way that the successive states visited form a Markov chain, and the particle stays in a given state a random amount of time depending on the state it is in as well as on the next state to be visited next.

TL;DR: In this article, the authors derived the asymptotic values of the first passage time distributions in the associated semi-Markov process, generalising the results of Kemeny and Snell [4] obtained for Markov chains.