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Optimal Inspection and Repair Policies for Infrastructure Facilities

Author

Listed:
  • Samer Madanat

    (School of Civil Engineering, Purdue University, West Lafayette, Indiana 47907)

  • Moshe Ben-Akiva

    (Civil Engineering Department, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

Abstract

State-of-the-art decision-making models in the area of infrastructure maintenance and rehabilitation (which are based on the Markov Decision Process) do not take into account the uncertainty in the measurement of facility condition. This paper presents a methodology, the Latent Markov Decision Process (LMDP), which explicitly recognizes the presence of random errors in the measurement of the condition of infrastructure facilities. Two versions of the LMDP are presented. In the first version, the inspection schedule is fixed, which is the usual assumption made in state-of-the-art models. The second version of the LMDP minimizes the sum of inspection and M & R costs. An empirical comparison of the two versions of the LMDP and the traditional MDP illustrates the importance of incorporating measurement uncertainty in decision-making and of optimizing the inspection schedule.

Suggested Citation

  • Samer Madanat & Moshe Ben-Akiva, 1994. "Optimal Inspection and Repair Policies for Infrastructure Facilities," Transportation Science, INFORMS, vol. 28(1), pages 55-62, February.
    • Handle: RePEc:inm:ortrsc:v:28:y:1994:i:1:p:55-62
    DOI: 10.1287/trsc.28.1.55
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    Citations

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    Cited by:

    1. 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.
    2. 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.
    3. Joaquim AP Braga & António R Andrade, 2019. "Optimizing maintenance decisions in railway wheelsets: A Markov decision process approach," Journal of Risk and Reliability, , vol. 233(2), pages 285-300, April.
    4. Zhang, Xueqing & Gao, Hui, 2012. "Road maintenance optimization through a discrete-time semi-Markov decision process," Reliability Engineering and System Safety, Elsevier, vol. 103(C), pages 110-119.
    5. Özgür-Ünlüakın, Demet & Bilgiç, Taner, 2017. "Performance analysis of an aggregation and disaggregation solution procedure to obtain a maintenance plan for a partially observable multi-component system," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 652-662.
    6. Lee, Jinwoo & Madanat, Samer, 2015. "A joint bottom-up solution methodology for system-level pavement rehabilitation and reconstruction," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 106-122.
    7. Mizutani, Daijiro & Nakazato, Yuto & Ikushima, Rie & Satsukawa, Koki & Kawasaki, Yosuke & Kuwahara, Masao, 2024. "Optimal intervention policy of emergency storage batteries for expressway transportation systems considering deterioration risk during lead time of replacement," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    8. Zhi-Chun Li & Dian Sheng, 2014. "Pavement rehabilitation scheduling and toll pricing under different regulatory regimes," Annals of Operations Research, Springer, vol. 217(1), pages 337-355, June.
    9. Kıvanç, İpek & Özgür-Ünlüakın, Demet & Bilgiç, Taner, 2022. "Maintenance policy analysis of the regenerative air heater system using factored POMDPs," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    10. 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.
    11. Papakonstantinou, K.G. & Shinozuka, M., 2014. "Planning structural inspection and maintenance policies via dynamic programming and Markov processes. Part II: POMDP implementation," Reliability Engineering and System Safety, Elsevier, vol. 130(C), pages 214-224.
    12. Rafic Faddoul & Abdul-Hamid Soubra & Wassim Raphael & Alaa Chateauneuf, 2013. "Extension of dynamic programming models for management optimization from single structure to multi-structures level," Post-Print hal-01006860, HAL.
    13. 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.
    14. Zhang, Le & Fu, Liangliang & Gu, Weihua & Ouyang, Yanfeng & Hu, Yaohua, 2017. "A general iterative approach for the system-level joint optimization of pavement maintenance, rehabilitation, and reconstruction planning," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 378-400.
    15. Papakonstantinou, K.G. & Shinozuka, M., 2014. "Planning structural inspection and maintenance policies via dynamic programming and Markov processes. Part I: Theory," Reliability Engineering and System Safety, Elsevier, vol. 130(C), pages 202-213.
    16. Seites-Rundlett, William & Bashar, Mohammad Z. & Torres-Machi, Cristina & Corotis, Ross B., 2022. "Combined evidence model to enhance pavement condition prediction from highly uncertain sensor data," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    17. 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.
    18. 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.
    19. 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.
    20. Madanat, S M & Durango, Pablo L, 2001. "Optimal maintenance and repair policies in infrastructure management under uncertain facility deterioration rates: an adaptive control approach," University of California Transportation Center, Working Papers qt8jz8h9fw, University of California Transportation Center.
    21. 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.

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