IDEAS home Printed from https://ideas.repec.org/p/cdl/uctcwp/qt1d85j6mt.html
   My bibliography  Save this paper

Robust Maintenance Policies for Markovian Systems under Model Uncertainty

Author

Listed:
  • Kuhn, Kenneth D.
  • Madanat, Samer M.

Abstract

Asset management systems help public works agencies decide when and how to maintain and rehabilitate infrastructure facilities in a cost effective manner. Many sources of error, some difficult to quantify, can limit the ability of asset management systems to accurately predict how built systems will deteriorate. This paper introduces the use of robust optimization to deal with epistemic uncertainty. The Hurwicz criterion is employed to ensure management policies are never ‘too conservative.’ An efficient solution algorithm is developed to solve robust counterparts of the asset management problem. A case study demonstrates how the consideration of uncertainty alters optimal management policies and shows how the proposed approach may reduce maintenance and rehabilitation (M&R) expenditures.

Suggested Citation

  • Kuhn, Kenneth D. & Madanat, Samer M., 2005. "Robust Maintenance Policies for Markovian Systems under Model Uncertainty," University of California Transportation Center, Working Papers qt1d85j6mt, University of California Transportation Center.
    • Handle: RePEc:cdl:uctcwp:qt1d85j6mt
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/1d85j6mt.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. John M. Mulvey & Robert J. Vanderbei & Stavros A. Zenios, 1995. "Robust Optimization of Large-Scale Systems," Operations Research, INFORMS, vol. 43(2), pages 264-281, April.
    2. Humplick, Frannie, 1992. "Highway pavement distress evaluation: Modeling measurement error," Transportation Research Part B: Methodological, Elsevier, vol. 26(2), pages 135-154, April.
    3. Prozzi, J A & Madanat, S M, 2004. "Development of Pavement Performance Models by Combining Experimental and Field Data," University of California Transportation Center, Working Papers qt6cf8v5cw, University of California Transportation Center.
    4. Samer Madanat & Moshe Ben-Akiva, 1994. "Optimal Inspection and Repair Policies for Infrastructure Facilities," Transportation Science, INFORMS, vol. 28(1), pages 55-62, February.
    Full references (including those not matched with items on IDEAS)

    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. Mishalani, Rabi G. & Gong, Liying, 2009. "Optimal infrastructure condition sampling over space and time for maintenance decision-making under uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 43(3), pages 311-324, March.
    2. Kuhn, Kenneth D. & Madanat, Samer M., 2005. "Model Uncertainty and the Management of a System of Infrastructure Facilities," University of California Transportation Center, Working Papers qt6c84b9b4, University of California Transportation Center.
    3. Durango-Cohen, Pablo L., 2007. "A time series analysis framework for transportation infrastructure management," Transportation Research Part B: Methodological, Elsevier, vol. 41(5), pages 493-505, June.
    4. Chu, Chih-Yuan & Durango-Cohen, Pablo L., 2008. "Estimation of dynamic performance models for transportation infrastructure using panel data," Transportation Research Part B: Methodological, Elsevier, vol. 42(1), pages 57-81, January.
    5. Durango-Cohen, Pablo L. & Madanat, Samer M., 2008. "Optimization of inspection and maintenance decisions for infrastructure facilities under performance model uncertainty: A quasi-Bayes approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(8), pages 1074-1085, October.
    6. Kobayashi, Kiyoshi & Kaito, Kiyoyuki & Lethanh, Nam, 2012. "A statistical deterioration forecasting method using hidden Markov model for infrastructure management," Transportation Research Part B: Methodological, Elsevier, vol. 46(4), pages 544-561.
    7. Moddassir Khan Nayeem & Gyu M. Lee, 2021. "Robust Design of Relief Distribution Networks Considering Uncertainty," Sustainability, MDPI, vol. 13(16), pages 1-24, August.
    8. Donghai Wang & Qiuhong Zhao, 2020. "A Simultaneous Optimization Model for Airport Network Slot Allocation under Uncertain Capacity," Sustainability, MDPI, vol. 12(14), pages 1-14, July.
    9. Ismail I. Almaraj & Theodore B. Trafalis, 2022. "A robust optimization approach in a multi-objective closed-loop supply chain model under imperfect quality production," Annals of Operations Research, Springer, vol. 319(2), pages 1479-1505, December.
    10. Shan Lan & John-Paul Clarke & Cynthia Barnhart, 2006. "Planning for Robust Airline Operations: Optimizing Aircraft Routings and Flight Departure Times to Minimize Passenger Disruptions," Transportation Science, INFORMS, vol. 40(1), pages 15-28, February.
    11. Surya Prakash & Sameer Kumar & Gunjan Soni & Vipul Jain & Ajay Pal Singh Rathore, 2020. "Closed-loop supply chain network design and modelling under risks and demand uncertainty: an integrated robust optimization approach," Annals of Operations Research, Springer, vol. 290(1), pages 837-864, July.
    12. Khaled, Oumaima & Minoux, Michel & Mousseau, Vincent & Michel, Stéphane & Ceugniet, Xavier, 2018. "A multi-criteria repair/recovery framework for the tail assignment problem in airlines," Journal of Air Transport Management, Elsevier, vol. 68(C), pages 137-151.
    13. Irawan, Chandra Ade & Jones, Dylan & Hofman, Peter S. & Zhang, Lina, 2023. "Integrated strategic energy mix and energy generation planning with multiple sustainability criteria and hierarchical stakeholders," European Journal of Operational Research, Elsevier, vol. 308(2), pages 864-883.
    14. Hashem Omrani & Farzane Adabi & Narges Adabi, 2017. "Designing an efficient supply chain network with uncertain data: a robust optimization—data envelopment analysis approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(7), pages 816-828, July.
    15. Somayyeh Lotfi & Stavros A. Zenios, 2024. "Robust mean-to-CVaR optimization under ambiguity in distributions means and covariance," Review of Managerial Science, Springer, vol. 18(7), pages 2115-2140, July.
    16. Roya Soltani & Seyed J Sadjadi, 2014. "Reliability optimization through robust redundancy allocation models with choice of component type under fuzziness," Journal of Risk and Reliability, , vol. 228(5), pages 449-459, October.
    17. Sprenger, Philipp & Parlings, Matthias & Hegmanns, Tobias, 2014. "Planning Approach for Robust Manufacturing Footprint Decisions," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), Next Generation Supply Chains: Trends and Opportunities. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 18, volume 18, pages 29-50, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    18. Jihee Han & KwangSup Shin, 2016. "Evaluation mechanism for structural robustness of supply chain considering disruption propagation," International Journal of Production Research, Taylor & Francis Journals, vol. 54(1), pages 135-151, January.
    19. Munoz, Francisco D. & van der Weijde, Adriaan Hendrik & Hobbs, Benjamin F. & Watson, Jean-Paul, 2017. "Does risk aversion affect transmission and generation planning? A Western North America case study," Energy Economics, Elsevier, vol. 64(C), pages 213-225.
    20. Huang, Edward & Liu, Irene & Lin, James T., 2018. "Robust model for the assignment of outgoing flights on airport baggage unloading areas," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 110-125.

    More about this item

    Keywords

    ;

    Statistics

    Access and download statistics

    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:cdl:uctcwp:qt1d85j6mt. 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: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/itucbus.html .

    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.