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Pontis: A System for Maintenance Optimization and Improvement of US Bridge Networks

Author

Listed:
  • Kamal Golabi

    (Optima, Incorporated, 55 Francisco Street, Suite 780, San Francisco, California 94133)

  • Richard Shepard

    (Office of Structure Maintenance, Department of Transportation, State of California, Sacramento, California 94274)

Abstract

Pontis provides a systematic methodology for allocating funds, evaluating current and future needs of bridges and options to meet those needs, and recommending the optimal policy for each bridge in the context of overall network benefits, budgets, and restrictions. After a trial implementation in California and extensive testing in several states, the system was adopted by AASHTO (Association of American State Highway Officials). Currently, over 40 states are implementing Pontis. At the heart of Pontis is a set of predictive and optimization models which derive their information from judgmental, engineering, and economic models and various databases. The predictive models start with engineering-based subjective inputs and update themselves in a Bayesian context as data is collected. The optimization models consist of interrelated Markov decision models and mathematical programming tools and models.

Suggested Citation

  • Kamal Golabi & Richard Shepard, 1997. "Pontis: A System for Maintenance Optimization and Improvement of US Bridge Networks," Interfaces, INFORMS, vol. 27(1), pages 71-88, February.
    • Handle: RePEc:inm:orinte:v:27:y:1997:i:1:p:71-88
    DOI: 10.1287/inte.27.1.71
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    Citations

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    Cited by:

    1. 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.
    2. Ugo Feunekes & Steve Palmer & Andrea Feunekes & John MacNaughton & Jay Cunningham & Kim Mathisen, 2011. "Taking the Politics Out of Paving: Achieving Transportation Asset Management Excellence Through OR," Interfaces, INFORMS, vol. 41(1), pages 51-65, February.
    3. Yu Fang & Lijun Sun, 2019. "Developing A Semi-Markov Process Model for Bridge Deterioration Prediction in Shanghai," Sustainability, MDPI, vol. 11(19), pages 1-15, October.
    4. Charles-Antoine Robelin & Samer M. Madanat, 2008. "Reliability-Based System-Level Optimization of Bridge Maintenance and Replacement Decisions," Transportation Science, INFORMS, vol. 42(4), pages 508-513, November.
    5. Robelin, Charles-Antoine & Madanat, S M, 2006. "Network-Level Reliability-Based Bridge Inspection, Maintenance and Replacement Optimization Model," University of California Transportation Center, Working Papers qt47v2652x, University of California Transportation Center.
    6. 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.
    7. Nakat, Z. & Madanat, S. & Farshidi, F. & Harvey, J., 2006. "Development of an Empirical-Mechanistic Model of Overlay Crack Progression using Data from the Washington State PMS Database," Institute of Transportation Studies, Working Paper Series qt0488k9kz, Institute of Transportation Studies, UC Davis.
    8. Pekka Mild & Ahti Salo, 2009. "Combining a Multiattribute Value Function with an Optimization Model: An Application to Dynamic Resource Allocation for Infrastructure Maintenance," Decision Analysis, INFORMS, vol. 6(3), pages 139-152, September.
    9. Kobayashi, K. & Kaito, K. & Lethanh, N., 2014. "A competing Markov model for cracking prediction on civil structures," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 345-362.
    10. 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.
    11. Mohit Tawarmalani & Yanjun Li, 2011. "Multi‐period maintenance scheduling of tree networks with minimum flow disruption," Naval Research Logistics (NRL), John Wiley & Sons, vol. 58(5), pages 507-530, August.
    12. Faddoul, R. & Raphael, W. & Chateauneuf, A., 2018. "Maintenance optimization of series systems subject to reliability constraints," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 179-188.
    13. 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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