A Fuzzy Queuing Model with Unreliable Server, Fuzzy Arrival and Service Rates, and Fuzzy Service Time.

AbstractThis paper presents a fuzzy queuing model that incorporates uncertainty in arrival and service rates, service time, and service reliability. The model is formulated as a fuzzy M/M/1 queuing system with an unreliable server, where the arrival rate, service rate, and service time are represented by fuzzy numbers. The server is assumed to be unreliable, with a fuzzy failure rate and fuzzy repair rate. Using fuzzy arithmetic and fuzzy calculus, We derive the fuzzy steady - state probabilities and performance metrices, such as the fuzzy expected number of customers in the system, fuzzy expected waiting time, and server utilization.Numerical examples are provided to illustrate the application of the model and the effects at fuzzy parameters on the performance metrices. The results show that the fuzzy queuing model can effectively capture the uncertainty and imprecision in the real world queuing system, providing a more realistic and robust analysis.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-08-25
DOI
https://doi.org/10.5281/zenodo.22091880
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

A Fuzzy Queuing Model with Unreliable Server, Fuzzy Arrival and Service Rates, and Fuzzy Service Time.

Kavita Kumari, Dr. Shaweta Sharma
Zenodo (CERN European Organization for Nuclear Research)
Advanced Queuing Theory Analysis
article

A Fuzzy Queuing Model with Unreliable Server, Fuzzy Arrival and Service Rates, and Fuzzy Service Time.

Kavita Kumari, Dr. Shaweta Sharma
article en

Abstract

AbstractThis paper presents a fuzzy queuing model that incorporates uncertainty in arrival and service rates, service time, and service reliability. The model is formulated as a fuzzy M/M/1 queuing system with an unreliable server, where the arrival rate, service rate, and service time are represented by fuzzy numbers. The server is assumed to be unreliable, with a fuzzy failure rate and fuzzy repair rate. Using fuzzy arithmetic and fuzzy calculus, We derive the fuzzy steady - state probabilities and performance metrices, such as the fuzzy expected number of customers in the system, fuzzy expected waiting time, and server utilization.Numerical examples are provided to illustrate the application of the model and the effects at fuzzy parameters on the performance metrices. The results show that the fuzzy queuing model can effectively capture the uncertainty and imprecision in the real world queuing system, providing a more realistic and robust analysis.

Zenodo (CERN European Organization for Nuclear Research)
Baba Mastnath University (IN)
Openalex Percentile: Top 5%
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.