Analysis and optimal control of a discrete-time queueing system under the (m,N)-policy

Authors:
Alfredo G. Hernández-Díaz;Pilar Moreno
Affiliations:
Universidad Pablo de Olavide, Sevilla, Spain;Universidad Pablo de Olavide, Sevilla, Spain
Venue:
valuetools '06 Proceedings of the 1st international conference on Performance evaluation methodolgies and tools
Year:
2006

Citing 5
Cited 2

Simultaneity in discrete-time single server queues with Bernoulli inputs

Performance Evaluation
Queue length and waiting time analysis of a batch arrival queue with bilevel control

Computers and Operations Research
Tabu Search

Tabu Search
Discrete-Time Models for Communication Systems Including ATM

Discrete-Time Models for Communication Systems Including ATM
Queueing networks with discrete time scale: explicit expressions for the steady state behavior of discrete time stochastic networks

Queueing networks with discrete time scale: explicit expressions for the steady state behavior of discrete time stochastic networks

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

ASMTA'10 Proceedings of the 17th international conference on Analytical and stochastic modeling techniques and applications
A discrete-time single-server queueing system with an N-policy, an early setup and a generalization of the Bernoulli feedback

Mathematical and Computer Modelling: An International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper analyzes a discrete-time single-server queue under bilevel threshold control and early setup. The joint generating function of the server state and the number of customers in the system together with the main performance measures are derived. We also study the length of the different busy periods of the server as well as the number of customers served during a busy period. We establish a cost model and find the optimal solution using a tabu search algorithm due the difficulty to prove the convexity of the cost function. Finally, we show some numerical examples to see the influence of the setup time distribution and the sensibility of the different costs.