IDEAS home Printed from https://ideas.repec.org/p/cdl/uctcwp/qt6c94v984.html
   My bibliography  Save this paper

History-Dependent Optimization of Bridge Maintenance and Replacement Decisions Using Markov Decision Process

Author

Listed:
  • Robelin, Charles-Antoine
  • Madanat, Samer M

Abstract

Bridge maintenance and replacement optimization methods use deterioration models to predict the future condition of bridge components. The purpose of this paper is to develop a framework for bridge maintenance optimization using a deterioration model that takes into account aspects of the history of the bridge condition and maintenance, while allowing the use of efficient optimization techniques. Markovian models are widely used to represent bridge component deterioration. In existing Markovian models, the state is the bridge component condition, and the history of the condition is not taken into account, which is seen as a limitation. This paper describes a method to formulate a realistic history-dependent model of bridge deck deterioration as a Markov chain, while retaining aspects of the history of deterioration and maintenance as part of the model. This model is then used to formulate and solve a reliability-based bridge maintenance optimization problem as a Markov decision process. A parametric study is conducted to compare the policies obtained in this research with policies derived using a simpler Markovian model.

Suggested Citation

  • Robelin, Charles-Antoine & Madanat, Samer M, 2007. "History-Dependent Optimization of Bridge Maintenance and Replacement Decisions Using Markov Decision Process," University of California Transportation Center, Working Papers qt6c94v984, University of California Transportation Center.
    • Handle: RePEc:cdl:uctcwp:qt6c94v984
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/6c94v984.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Durango, Pablo L. & Madanat, Samer M., 2002. "Optimal maintenance and repair policies in infrastructure management under uncertain facility deterioration rates: an adaptive control approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 36(9), pages 763-778, November.
    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. Orcesi, André D. & Cremona, Christian F., 2010. "A bridge network maintenance framework for Pareto optimization of stakeholders/users costs," Reliability Engineering and System Safety, Elsevier, vol. 95(11), pages 1230-1243.
    2. Rafic Faddoul & Wassim Raphael & Abdul-Hamid Soubra & Alaa Chateauneuf, 2013. "Incorporating Bayesian networks in Markov Decision Processes," Post-Print hal-01006963, HAL.
    3. Yingnan Yang & Hongming Xie, 2021. "Determination of Optimal MR&R Strategy and Inspection Intervals to Support Infrastructure Maintenance Decision Making," Sustainability, MDPI, vol. 13(5), pages 1-10, 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. Seyedshohadaie, S. Reza & Damnjanovic, Ivan & Butenko, Sergiy, 2010. "Risk-based maintenance and rehabilitation decisions for transportation infrastructure networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(4), pages 236-248, May.
    2. Pantha, Bhoj Raj & Yatabe, Ryuichi & Bhandary, Netra Prakash, 2010. "GIS-based highway maintenance prioritization model: an integrated approach for highway maintenance in Nepal mountains," Journal of Transport Geography, Elsevier, vol. 18(3), pages 426-433.
    3. Robelin, Charles-Antoine, 2006. "Facility-Level and System-Level Stochastic Optimization of Bridge Maintenance Policies for Markovian Management Systems," University of California Transportation Center, Working Papers qt0475p5qp, University of California Transportation Center.
    4. Wen, Qi & Qiang, Maoshan & Xia, Bingqing & An, Nan, 2019. "Discovering regulatory concerns on bridge management: An author-topic model based approach," Transport Policy, Elsevier, vol. 75(C), pages 161-170.
    5. Bismut, Elizabeth & Straub, Daniel, 2021. "Optimal adaptive inspection and maintenance planning for deteriorating structural systems," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    6. Chootinan, Piya & Chen, Anthony & Horrocks, Matthew R. & Bolling, Doyt, 2006. "A multi-year pavement maintenance program using a stochastic simulation-based genetic algorithm approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(9), pages 725-743, November.
    7. 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.
    8. González, Javier & Romera, Rosario & Pérez, Jose M., 2006. "Optimal railway infrastructure maintenance and repair policies to manage risk under uncertainty with adaptive control," DES - Working Papers. Statistics and Econometrics. WS ws061605, Universidad Carlos III de Madrid. Departamento de Estadística.
    9. Park, Sejung, 2004. "Optimal Infrastructure System Maintenance and Repair Policies with Random Deterioration Model Parameters," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt2g6850jc, Institute of Transportation Studies, UC Berkeley.
    10. 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.
    11. Memarzadeh, Milad & Pozzi, Matteo & Kolter, J. Zico, 2016. "Hierarchical modeling of systems with similar components: A framework for adaptive monitoring and control," Reliability Engineering and System Safety, Elsevier, vol. 153(C), pages 159-169.
    12. 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.
    13. Bismut, Elizabeth & Pandey, Mahesh D. & Straub, Daniel, 2022. "Reliability-based inspection and maintenance planning of a nuclear feeder piping system," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    14. Arcieri, Giacomo & Hoelzl, Cyprien & Schwery, Oliver & Straub, Daniel & Papakonstantinou, Konstantinos G. & Chatzi, Eleni, 2023. "Bridging POMDPs and Bayesian decision making for robust maintenance planning under model uncertainty: An application to railway systems," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    15. Madanat, S M & Park, Sejung & Kuhn, K D, 2006. "Adaptive Optimization and Systematic Probing of Infrastructure System Maintenance Policies under Model Uncertainty," University of California Transportation Center, Working Papers qt4fb7k5rc, University of California Transportation Center.

    More about this item

    Keywords

    Social and Behavioral Sciences;

    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:qt6c94v984. 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.