Transient analysis and ANFIS computing of unreliable single server queueing model with multiple stage service and functioning vacation

Ahuja, Anjali; Jain, Anamika; Jain, Madhu

doi:10.1016/j.matcom.2021.09.011

Cited by 19 publications

(3 citation statements)

References 26 publications

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“…ANFIS was established in the early 1980s by Professor Lotfi A. Zadeh [26]. Ahuja et al [2] presented a comprehensive analysis of a single server queueing model with multiple stage service and functioning vacation, focusing on transient behavior. Additionally, they employed ANFIS computing techniques to enhance their analysis.…”

Section: Survey Of Literaturementioning

confidence: 99%

Heterogeneous Server Retrial Queueing Model With Feedback and Working Vacation Using Artificial Bee Colony Optimization Algorithm

Divya,

Indhira

2023

UMJ

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This research delves into the dynamics of a retrial queueing system featuring heterogeneous servers with intermittent availability, incorporating feedback and working vacation mechanisms. Employing a matrix geometric approach, this study establishes the steady-state probability distribution for the queue size in this complex heterogeneous service model. Additionally, a range of system performance metrics is developed, alongside the formulation of a cost function to evaluate decision variable optimization within the service system. The Artificial Bee Colony (ABC) optimization algorithm is harnessed to determine service rates that minimize the overall cost. This work includes numerical examples and sensitivity analyses to validate the model's effectiveness. Also, a comparison between the numerical findings and the neuro-fuzzy results has been examined by the adaptive neuro fuzzy interface system (ANFIS).

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Section: Survey Of Literaturementioning

confidence: 99%

Heterogeneous Server Retrial Queueing Model With Feedback and Working Vacation Using Artificial Bee Colony Optimization Algorithm

Divya,

Indhira

2023

UMJ

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“…In this research, a phase-type distribution is used to represent the service times. Ahuja et al (2021) investigated a single server queueing model that is unreliable, as well as multiple-stage service and functioning vacation. Bhagat et al (2021) studied a machine repair problem (MRP) with M identical operating machines and control arrival policy.…”

Section: Introductionmentioning

confidence: 99%

Vacation Policy for k-out-of-n Redundant System with Reboot Delay

Tyagi,

Ram,

Manglik

et al. 2024

Int. j. math. eng. manag. sci.

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Redundancy is a well-known concept for system resilience; k-out-of-n redundancy stipulates that a minimum number of functional components must be present for the system to function. Introducing a reboot delay acknowledges the temporal complexities of system recovery after a failure. A dynamic component is added by the vacation policy, which introduces strategic downtime for system components. This work predicts the performance measures of a multi-state system consisting of two subsystems A and B. Subsystem A follows the k-out-of-n: F policy and subsystem B has m working units and s warm standby units. The system is under the consideration of a single unreliable repairman who may go allow for vacation. There are two possibilities for a repairman’s vacation: if the system failed and the repairman is on vacation, in that case, if the repairman immediately returns from vacation, he/ she repairs the system but if the repairman does not return immediately from vacation, then the system takes a reboot action and when the repairman available, he/ she repairs the system. Failure and repair time of the units are expected to pursue an exponential distribution. In addition, the vacation time and reboot time regarding the failure of the units also pursue an exponential distribution. The concept of reboot and repairman’s vacation are incorporated to make the model more practical and versatile. The expressions for several performance measures such as availability, reliability, and MTTF are obtained with the help of the Markov process. Likewise, sensitivity analysis is done to study the impact of various parameters on system performance measures. The results are explained by taking numerical illustrations.

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“…MTTF, availability and reliability of machines where the server may take multiple vacations during the operation considered by the authors 24) . The multi-components queueing system and optimized cost function in various research paper and displayed results through numerical illustration in tabular form are carried out by the authors [3][4][5][6] .…”

Section: Introductionmentioning

confidence: 99%

Optimization of Multicomponent Machine System with Reneging

Praveen Kumar Agrawal,

Jain,

Thakur

2023

Evergreen

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The system reliability of a multi-spares repairable system with reneging under "N-Policy" is considered. There is a provision of warm and cold reserve units and single repairman. Spares are designed to have exponentially distributed life durations and restoration times. A set of differential-difference equations has been constructed in terms of state dependent letdown and restoration rates. The time dependent analysis has been provided to obtain the states probabilities and to determine 'system reliability' and 'mean time to failure'. Laplace transform of the equations and the matrix technique is used to obtain the probabilities. The cost optimization is also presented. Optimal system parameters have been obtained using a heuristic approach. Various performance indices will be evaluated to explore the outcome of different strictures on the system reliability and 'mean time to failure'.

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Transient analysis and ANFIS computing of unreliable single server queueing model with multiple stage service and functioning vacation

Cited by 19 publications

References 26 publications

Heterogeneous Server Retrial Queueing Model With Feedback and Working Vacation Using Artificial Bee Colony Optimization Algorithm

Heterogeneous Server Retrial Queueing Model With Feedback and Working Vacation Using Artificial Bee Colony Optimization Algorithm

Vacation Policy for k-out-of-n Redundant System with Reboot Delay

Optimization of Multicomponent Machine System with Reneging

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