GENERAL DECREMENTING SERVICE POLICY IN THE GEOM/G/1 QUEUEING MODEL WITH MULTIPLE ADAPTIVE VACATIONS AND SETUP TIME

This paper analyses a discrete-time Geom/G/1 queue in which the server follows a general decrementing (GD) service rule, takes multiple adaptive vacations (MAV) whenever a service period ends, and needs a setup time before service is resumed. By means of an embedded Markov chain observed at vacation completion instants, combined with a regenerative-cycle argument, the probability generating functions (PGFs) of the stationary number of customers and of the stationary waiting time are derived, and each of them is shown to decompose stochastically into independent components. By specialising the parameters H and K, several classical vacation schemes are recovered as particular cases of the present policy. Numerical experiments then compare the expected number of customers and the expected waiting time across these particular cases. Setup time is added in general decrementing service policy to find the various characteristics.

Authors

Publication Details

Journal
Acta Innovations
Published
2026-11-03
DOI
https://doi.org/10.62441/actainnovations.vi.3015
Primary Topic
Advanced Queuing Theory Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

GENERAL DECREMENTING SERVICE POLICY IN THE GEOM/G/1 QUEUEING MODEL WITH MULTIPLE ADAPTIVE VACATIONS AND SETUP TIME

E. Rameshkumar, P. Sheela pappy
Acta Innovations
Advanced Queuing Theory Analysis
article

GENERAL DECREMENTING SERVICE POLICY IN THE GEOM/G/1 QUEUEING MODEL WITH MULTIPLE ADAPTIVE VACATIONS AND SETUP TIME

E. Rameshkumar, P. Sheela pappy
article en

Abstract

This paper analyses a discrete-time Geom/G/1 queue in which the server follows a general decrementing (GD) service rule, takes multiple adaptive vacations (MAV) whenever a service period ends, and needs a setup time before service is resumed. By means of an embedded Markov chain observed at vacation completion instants, combined with a regenerative-cycle argument, the probability generating functions (PGFs) of the stationary number of customers and of the stationary waiting time are derived, and each of them is shown to decompose stochastically into independent components. By specialising the parameters H and K, several classical vacation schemes are recovered as particular cases of the present policy. Numerical experiments then compare the expected number of customers and the expected waiting time across these particular cases. Setup time is added in general decrementing service policy to find the various characteristics.

Acta InnovationsVol. 64(2s)
Openalex Percentile: Top 9%
Advanced Queuing Theory Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon