Computational approach for transient behaviour of M /M (a, b) /1 bulk service queueing system with standby server

2022 ◽  
Author(s):  
S. Shanthi ◽  
Muthu Ganapathi Subramanian ◽  
Gopal Sekar
Keyword(s):  
Queueing System ◽  
Computational Approach ◽  
Transient Behaviour ◽  
Bulk Service

scholarly journals A queueing system with single arrival bulk service and single departure

2000 ◽  
Vol 31 (2-3) ◽  
pp. 99-108 ◽  
Author(s):  
A. Krishnamoorthy ◽  
P.V. Ushakumari
Keyword(s):  
Queueing System ◽  
Bulk Service

Computation of the stationary distribution of the queue size in an M/G/1 queueing system with variable service rate

1980 ◽  
Vol 17 (2) ◽  
pp. 515-522 ◽  
Author(s):  
A. Federgruen ◽  
H. C. Tijms
Keyword(s):  
Stationary Distribution ◽  
Queueing System ◽  
Computational Approach ◽  
Service Rate ◽  
Queue Size ◽  
Stationary Probabilities

This paper presents a simple and computationally tractable method which recursively computes the stationary probabilities of the queue size in an M/G/1 queueing system with variable service rate. For each service two possible service types are available and the service rule is characterized by two switch-over levels. The computational approach discussed in this paper can be applied to a variety of queueing problems.

scholarly journals On a bulk queueing system with impatient customers

1998 ◽  
Vol 3 (6) ◽  
pp. 539-554 ◽  
Author(s):  
Lotfi Tadj ◽  
Lakdere Benkherouf ◽  
Lakhdar Aggoun
Keyword(s):  
Steady State ◽  
Queue Length ◽  
Queueing System ◽  
Impatient Customers ◽  
Ergodicity Condition ◽  
Bulk Service ◽  
Bulk Arrival ◽  
Steady State Probabilities ◽  
System Characteristics

We consider a bulk arrival, bulk service queueing system. Customers are served in batches ofrunits if the queue length is not less thanr. Otherwise, the server delays the service until the number of units in the queue reaches or exceeds levelr. We assume that unserved customers may get impatient and leave the system. An ergodicity condition and steady-state probabilities are derived. Various system characteristics are also computed.

scholarly journals Analysis of Flexible Batch Service Queueing System to Constrict Waiting Time of Customers

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Deena Merit C. K. ◽  
Haridass M
Keyword(s):  
Arrival Time ◽  
Queueing System ◽  
Clinical Laboratory ◽  
Waiting Times ◽  
Distribution Center ◽  
Expiration Date ◽  
Suggested Model ◽  
Numerical Illustration ◽  
Bulk Service ◽  
Number Of Customers

When the required number of customers is available in the general bulk service (GBS) queueing system, the server begins service. Otherwise, the server will remain inactive until the number of consumers in the queue reaches that minimum required number. Customers that have already come must wait throughout this time, regardless of their arrival time. In some circumstances, like specimens awaiting testing in a clinical laboratory or perishable commodities awaiting delivery, it is necessary to finish services before the expiration date. It might only be achievable if consumers’ waiting times are kept under control. As a result, the flexible general bulk service (FGBS) rule is developed in this article to provide flexibility in batching. The effectiveness of FGBS implementation has been demonstrated using two examples: a clinical laboratory and a distribution center. To justify the suggested model, a simulation study and numerical illustration are provided.

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