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N-policy for redundant machining system with double retrial orbits using soft computing techniques.

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Title: N-policy for redundant machining system with double retrial orbits using soft computing techniques.
Authors: Singh, Vijay Pratap1 (AUTHOR) vsingh3@ma.iitr.ac.in, Jain, Madhu1 (AUTHOR) madhu.jain@ma.iitr.ac.in, Sharma, Richa2 (AUTHOR) richasharma@jklu.edu.in
Source: Mathematics & Computers in Simulation. Nov2025, Vol. 237, p42-69. 28p.
Subjects: Matrix analytic methods, Computer network traffic, Telecommunication traffic, Metaheuristic algorithms, Particle swarm optimization
Abstract: The present study is concerned with the performance prediction of a double retrial orbit redundant repairable machining system. Both primary and secondary orbits are available as waiting/buffer space for the failed units. In these orbits, the failed units can reside and make re-attempts for the repair. As per N-policy, if there are no units in the orbits for the repairing job, the repairman goes on vacation and further starts the repair job when N-failed units are accumulated. The objective of this investigation is to evaluate the transient and steady-state distributions of the queue length of failed units under N-policy. The matrix analytic and matrix recursive methods are utilized for solution purpose while an adaptive neuro-fuzzy inference system (ANFIS) is employed for validating the feasibility of designing the AI-based controller. The harmonic search (HS) and particle swarm optimization (PSO) methods have been implemented for the cost optimization purpose so as to evaluate the optimal design parameters. The outputs of study provides critical insights into optimal system performance and improving the repair policy. Furthermore, a practical application of this investigation is demonstrated in a telecommunications network traffic system, where the proposed methods can be utilized to manage the maintenance issues of routers in the network traffic. • Double retrial orbits Markovian queueing model under N -policy has been investigated. • The realistic features of imperfect service and unreliable server are incorporated. • Matrix analytic and matrix methods are used for solving the transient and steady-state queue size distributions. • The soft computing techniques ANFIS, PSO, and HS have been implemented. • This article illustrates the maintenance of network traffic system. [ABSTRACT FROM AUTHOR]
Copyright of Mathematics & Computers in Simulation is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
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  Data: N-policy for redundant machining system with double retrial orbits using soft computing techniques.
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  Data: <searchLink fieldCode="AR" term="%22Singh%2C+Vijay+Pratap%22">Singh, Vijay Pratap</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> vsingh3@ma.iitr.ac.in</i><br /><searchLink fieldCode="AR" term="%22Jain%2C+Madhu%22">Jain, Madhu</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> madhu.jain@ma.iitr.ac.in</i><br /><searchLink fieldCode="AR" term="%22Sharma%2C+Richa%22">Sharma, Richa</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> richasharma@jklu.edu.in</i>
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  Data: <searchLink fieldCode="JN" term="%22Mathematics+%26+Computers+in+Simulation%22">Mathematics & Computers in Simulation</searchLink>. Nov2025, Vol. 237, p42-69. 28p.
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  Data: <searchLink fieldCode="DE" term="%22Matrix+analytic+methods%22">Matrix analytic methods</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+network+traffic%22">Computer network traffic</searchLink><br /><searchLink fieldCode="DE" term="%22Telecommunication+traffic%22">Telecommunication traffic</searchLink><br /><searchLink fieldCode="DE" term="%22Metaheuristic+algorithms%22">Metaheuristic algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Particle+swarm+optimization%22">Particle swarm optimization</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: The present study is concerned with the performance prediction of a double retrial orbit redundant repairable machining system. Both primary and secondary orbits are available as waiting/buffer space for the failed units. In these orbits, the failed units can reside and make re-attempts for the repair. As per N-policy, if there are no units in the orbits for the repairing job, the repairman goes on vacation and further starts the repair job when N-failed units are accumulated. The objective of this investigation is to evaluate the transient and steady-state distributions of the queue length of failed units under N-policy. The matrix analytic and matrix recursive methods are utilized for solution purpose while an adaptive neuro-fuzzy inference system (ANFIS) is employed for validating the feasibility of designing the AI-based controller. The harmonic search (HS) and particle swarm optimization (PSO) methods have been implemented for the cost optimization purpose so as to evaluate the optimal design parameters. The outputs of study provides critical insights into optimal system performance and improving the repair policy. Furthermore, a practical application of this investigation is demonstrated in a telecommunications network traffic system, where the proposed methods can be utilized to manage the maintenance issues of routers in the network traffic. • Double retrial orbits Markovian queueing model under N -policy has been investigated. • The realistic features of imperfect service and unreliable server are incorporated. • Matrix analytic and matrix methods are used for solving the transient and steady-state queue size distributions. • The soft computing techniques ANFIS, PSO, and HS have been implemented. • This article illustrates the maintenance of network traffic system. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Mathematics & Computers in Simulation is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1016/j.matcom.2025.04.025
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      – Code: eng
        Text: English
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        PageCount: 28
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      – SubjectFull: Matrix analytic methods
        Type: general
      – SubjectFull: Computer network traffic
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      – SubjectFull: Telecommunication traffic
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      – SubjectFull: Metaheuristic algorithms
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      – SubjectFull: Particle swarm optimization
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      – TitleFull: N-policy for redundant machining system with double retrial orbits using soft computing techniques.
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            NameFull: Singh, Vijay Pratap
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            NameFull: Jain, Madhu
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            NameFull: Sharma, Richa
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            – D: 01
              M: 11
              Text: Nov2025
              Type: published
              Y: 2025
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