IDEAS home Printed from https://ideas.repec.org/a/pal/jorsoc/v61y2010i7d10.1057_jors.2009.40.html
   My bibliography  Save this article

Quantifying the risk in age and block replacement policies

Author

Listed:
  • B C Giri

    (Jadavpur University)

  • T Dohi

    (Hiroshima University)

Abstract

Preventive maintenance policies have been studied in the literature without considering the risk due to the cost variability. In this paper, we consider the two most popular preventive replacement policies, namely, age and block replacement policies under long-run average cost and expected unit time cost criteria. To quantify the risk in the preventive maintenance policies, we use the long-run variance of the accumulated cost over a time interval. We numerically derive the Risk-sensitive preventive replacement policies and study the impact of the Risk-sensitive optimality criterion on the managerial decisions. We also examine the performance of the expected unit time cost criterion as an alternative to the traditional long-run average cost criterion.

Suggested Citation

  • B C Giri & T Dohi, 2010. "Quantifying the risk in age and block replacement policies," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(7), pages 1151-1158, July.
  • Handle: RePEc:pal:jorsoc:v:61:y:2010:i:7:d:10.1057_jors.2009.40
    DOI: 10.1057/jors.2009.40
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/jors.2009.40
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1057/jors.2009.40?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Pulley, Lawrence B., 1981. "A General Mean-Variance Approximation to Expected Utility for Short Holding Periods," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 16(3), pages 361-373, September.
    2. Levy, H & Markowtiz, H M, 1979. "Approximating Expected Utility by a Function of Mean and Variance," American Economic Review, American Economic Association, vol. 69(3), pages 308-317, June.
    3. Richard Barlow & Larry Hunter, 1960. "Optimum Preventive Maintenance Policies," Operations Research, INFORMS, vol. 8(1), pages 90-100, February.
    4. John G. Wilson, 1996. "A Note on Variance Reducing Group Maintenance Policies," Management Science, INFORMS, vol. 42(3), pages 452-456, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jiang, R., 2018. "Performance evaluation of seven optimization models of age replacement policy," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 302-311.
    2. Jingyi Zhao & Chunhai Gao & Tao Tang, 2022. "A Review of Sustainable Maintenance Strategies for Single Component and Multicomponent Equipment," Sustainability, MDPI, vol. 14(5), pages 1-22, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Guo, Xu & Lien, Donald & Wong, Wing-Keung, 2015. "Good Approximation of Exponential Utility Function for Optimal Futures Hedging," MPRA Paper 66841, University Library of Munich, Germany.
    2. Harry Markowitz & Joseph Blasi & Douglas Kruse, 2010. "Employee stock ownership and diversification," Annals of Operations Research, Springer, vol. 176(1), pages 95-107, April.
    3. Eric Jondeau & Michael Rockinger, 2005. "Conditional Asset Allocation under Non-Normality: How Costly is the Mean-Variance Criterion?," FAME Research Paper Series rp132, International Center for Financial Asset Management and Engineering.
    4. David Johnstone, 2002. "Behavioral and Prescriptive Explanations of a Reverse Sunk Cost Effect," Theory and Decision, Springer, vol. 53(3), pages 209-242, November.
    5. Gourieroux, C. & Jouneau, F., 1999. "Econometrics of efficient fitted portfolios," Journal of Empirical Finance, Elsevier, vol. 6(1), pages 87-118, January.
    6. Bernard V. Tew & Donald W. Reid, 1987. "More Evidence On Expected Value-Variance Analysis Versus Direct Utility Maximization," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 10(3), pages 249-257, September.
    7. António Alberto Santos & Ana Margarida Monteiro & Rui Pascoal, 2014. "Portfolio Choice under Parameter Uncertainty: Bayesian Analysis and Robust Optimization Comparison," GEMF Working Papers 2014-25, GEMF, Faculty of Economics, University of Coimbra.
    8. Estada, Javier, 2003. "Mean-semivariance behavior: An alternative behavioral model," IESE Research Papers D/492, IESE Business School.
    9. Duane Rockerbie & Stephen Easton, 2018. "Revenue Sharing in Major League Baseball: The Moments That Meant so Much," IJFS, MDPI, vol. 6(3), pages 1-16, August.
    10. Kassimatis, Konstantinos, 2021. "Mean-variance versus utility maximization revisited: The case of constant relative risk aversion," International Review of Financial Analysis, Elsevier, vol. 78(C).
    11. Harry M. Markowitz, 2002. "Efficient Portfolios, Sparse Matrices, and Entities: A Retrospective," Operations Research, INFORMS, vol. 50(1), pages 154-160, February.
    12. Eric Jondeau & Michael Rockinger, 2006. "Optimal Portfolio Allocation under Higher Moments," European Financial Management, European Financial Management Association, vol. 12(1), pages 29-55, January.
    13. Li, Chenguang & Sexton, Richard J., 2009. "Impacts of Retailers’ Pricing Strategies for Produce Commodities on Farmer Welfare," 2009 Conference, August 16-22, 2009, Beijing, China 51720, International Association of Agricultural Economists.
    14. Markowitz, Harry, 2014. "Mean–variance approximations to expected utility," European Journal of Operational Research, Elsevier, vol. 234(2), pages 346-355.
    15. Silva, A. Christian & Prange, Richard E., 2007. "Virtual volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 376(C), pages 507-516.
    16. Caiyun Niu & Xiaolin Liang & Bingfeng Ge & Xue Tian & Yingwu Chen, 2016. "Optimal replacement policy for a repairable system with deterioration based on a renewal-geometric process," Annals of Operations Research, Springer, vol. 244(1), pages 49-66, September.
    17. Finkelstein, Maxim & Cha, Ji Hwan & Langston, Amy, 2023. "Improving classical optimal age-replacement policies for degrading items," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    18. Guo R. & Ascher H. & Love E., 2001. "Towards Practical and Synthetical Modelling of Repairable Systems," Stochastics and Quality Control, De Gruyter, vol. 16(1), pages 147-182, January.
    19. Chattopadhyay, Gopinath & Rahman, Anisur, 2008. "Development of lifetime warranty policies and models for estimating costs," Reliability Engineering and System Safety, Elsevier, vol. 93(4), pages 522-529.
    20. Junyuan Wang & Jimin Ye & Qianru Ma & Pengfei Xie, 2022. "An extended geometric process repairable model with its repairman having vacation," Annals of Operations Research, Springer, vol. 311(1), pages 401-415, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:jorsoc:v:61:y:2010:i:7:d:10.1057_jors.2009.40. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave-journals.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.