1979
DOI: 10.1287/moor.4.2.162
|View full text |Cite
|
Sign up to set email alerts
|

Reneging Phenomena in Single Channel Queues

Abstract: We consider a GI/G/1 queueing system where the nth arrival may renege if his service does not commence before an elapsed random time Zn. Results for the general case include relations analogous to Little's formula L = λW, an expression for the average fraction of customers who renege from the system, expressions for the waiting time distribution for all arrivals to the system, the waiting time distribution for arrivals who reach the server, the distribution for virtual waiting time in the queue, and the distri… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4

Citation Types

0
49
0

Year Published

1985
1985
2014
2014

Publication Types

Select...
5
4
1

Relationship

0
10

Authors

Journals

citations
Cited by 108 publications
(49 citation statements)
references
References 22 publications
0
49
0
Order By: Relevance
“…Daley [10] studied the GI/G/1 + G queue by setting up an integral equation for the waiting time distribution and focused on M/G/1 + D and M/G/1 + M (where +M refers to the exponential impatience time) queues. The GI/G/1 + G queue was also studied by Baccelli et al [3] and Stanford [18,19], and results for actual and virtual waiting times were obtained. This paper is inspired by de Kok and Tijms [15] and Xiong et al [21] who studied the M/G/1+D queue.…”
Section: Introductionmentioning
confidence: 99%
“…Daley [10] studied the GI/G/1 + G queue by setting up an integral equation for the waiting time distribution and focused on M/G/1 + D and M/G/1 + M (where +M refers to the exponential impatience time) queues. The GI/G/1 + G queue was also studied by Baccelli et al [3] and Stanford [18,19], and results for actual and virtual waiting times were obtained. This paper is inspired by de Kok and Tijms [15] and Xiong et al [21] who studied the M/G/1+D queue.…”
Section: Introductionmentioning
confidence: 99%
“…Stanford [11] relates the waiting time distribution of the (successful) customers and the workload seen by an arbitrary arrival in G/G/1 + G. See Stanford [12] for a brief literature review, and [5] for an approximation for the waiting time distribution in M/G/N + G and several additional references on multiserver queues with impatience.…”
Section: Introductionmentioning
confidence: 99%
“…(See also Stanford [22] and Boots and Tijms [6].) This literature focuses on exact performance analysis of the system involved.…”
Section: Introductionmentioning
confidence: 99%