Skip to main content
SpringerLink
Log in

Performance Modeling and ANFIS Computing for Finite Buffer Retrial Queue Under F-Policy

  • Conference paper
  • First Online:
Proceedings of Sixth International Conference on Soft Computing for Problem Solving

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 547))

Abstract

This investigation is concerned with the performance prediction and admission control F-policy for the machine repair problem with retrial. To develop a Markov model, the steady state Chapman-Kolmogorov equations are constructed. The system state probabilities are obtained by using recursive method. Various performance measures are established explicitly in terms of steady state probabilities. To examine the effects of system parameters, the numerical simulation is performed by choosing a suitable illustration. The cost function is also framed to evaluate the optimal service rate and corresponding optimal cost. ANFIS soft computing technique is used to compare the numerical results obtained analytically and also by implementing ANFIS.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Artalejo, J.R., Falin, G.I.: Standard and retrial queueing systems: A comparative analysis. Rev. Mat. Complutense 15, 101–129 (2002)

    MathSciNet  MATH  Google Scholar 

  2. Artalejo, J.R.: Accessible bibliography on retrial queues. Math. Comput. Model. 51, 1071–1081 (2010)

    Article  MATH  Google Scholar 

  3. Sherman, N.P., Kharoufeh, J.P.: An M/M/1 retrial queue with unreliable server. Oper. Res. Lett. 69, 697–705 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  4. Gupta, S.M.: Machine interference problem with warm spares, server vacations and exhaustive service. Perform. Eval. 29, 195–211 (1997)

    Article  Google Scholar 

  5. Wang, K.H., Chen, W.L., Yang, D.Y.: Optimal management of the machine repair problem with working vacation: newton’s method. J. Comput. Appl. Math. 233, 449–458 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  6. Wang, K.H., Siwazlian, B.D.: Cost analysis of the M/M/R machine repair problem with spares operating under variable service rates. Microelectron. Reliab. 32, 1171–1183 (1992)

    Article  Google Scholar 

  7. Wang, K.H.: Cost analysis of the M/M/R machine-repair problem with mixed standby spares. Microelectron. Reliab. 33, 1293–1301 (1993)

    Article  Google Scholar 

  8. Jain, M.: An (m, M) machine repair problem with spares and state dependent rates: a diffusion process approach. Microelectron. Reliab. 37, 929–933 (1997)

    Article  Google Scholar 

  9. Yang, D.Y., Chiang, Y.C.: An evolutionary algorithm for optimizing the machine repair problem under a threshold recovery policy. J. Chin. Inst. Eng. 37, 224–231 (2014)

    Article  Google Scholar 

  10. Gupta, S.M.: Interrelationship between controlling arrival and service in queueing systems. Comput. Oper. Res. 22, 1005–1014 (1995)

    Article  MATH  Google Scholar 

  11. Yang, Y.D., Wang, K.H., Wu, C.H.: Optimization and sensitivity analysis of controlling arrivals in the queueing system with single working vacation. J. Comput. Appl. Math. 234, 545–556 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  12. Wang, K.H., Yang, D.Y.: Controlling arrivals for a queueing system with an unreliable server Newton-Quasi method. Appl. Math. Comput. 213, 92–101 (2009)

    MathSciNet  MATH  Google Scholar 

  13. Jain, M., Bhagat, A.: Transient analysis of finite F-policy retrial queues with delay repair and threshold recovery. Natl. Acad. Sci. Lett. 38, 257–261 (2015)

    Article  Google Scholar 

  14. Goswami, V.: Relationship between randomized F-policy and randomized N-policy in discrete-time queues. OPSEARCH 53, 131–150 (2016)

    Article  MathSciNet  Google Scholar 

  15. Lin, Z.C., Liu, C.Y.: Application of an adaptive neuro-fuzzy inference system for the optimal analysis of chemical–mechanical polishing process parameters. Int. J. Adv. Manufact. Technol. 18, 20–28 (2003)

    Article  Google Scholar 

  16. Jain, M., Upadhyaya, S.: Threshold N-Policy for degraded machining system with multiple type spares and multiple vacations. Qual. Technol. Quant. Manag. 6, 185–203 (2009)

    Article  MathSciNet  Google Scholar 

  17. Kumar, K., Jain, M.: Threshold N-policy for (M, m) degraded machining system with K-heterogeneous server, standby switching failure and multiple vacation. Int. J. Math. Oper. Res. 5, 423–445 (2013)

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mathematics, IIT Roorkee, Roorkee, 247 667, India

    Madhu Jain & Sudeep Singh Sanga

Authors
  1. Madhu Jain
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sudeep Singh Sanga
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sudeep Singh Sanga .

Editor information

Editors and Affiliations

  1. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, India

    Kusum Deep

  2. Department of Mathematics, South Asian University, New Delhi, India

    Jagdish Chand Bansal

  3. Department of Mathematics, National Institute of Technology, Silchar, Silchar, Assam, India

    Kedar Nath Das

  4. School of Mathematics, Thapar Institute of Engineering and Technology University, Patiala, Punjab, India

    Arvind Kumar Lal

  5. School of Mathematics, Thapar Institute of Engineering and Technology University, Patiala, Punjab, India

    Harish Garg

  6. Department of Mathematics and Computer Science, Liverpool Hope University, Liverpool, United Kingdom

    Atulya K. Nagar

  7. Department of Paper Technology, Indian Institute of Technology Roorkee, Roorkee, India

    Millie Pant

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer Nature Singapore Pte Ltd.

About this paper

Cite this paper

Jain, M., Sanga, S.S. (2017). Performance Modeling and ANFIS Computing for Finite Buffer Retrial Queue Under F-Policy. In: Deep, K., et al. Proceedings of Sixth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 547. Springer, Singapore. https://doi.org/10.1007/978-981-10-3325-4_25

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-3325-4_25

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3324-7

  • Online ISBN: 978-981-10-3325-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation