IDEAS home Printed from https://ideas.repec.org/p/cdl/uctcwp/qt6c84b9b4.html
   My bibliography  Save this paper

Model Uncertainty and the Management of a System of Infrastructure Facilities

Author

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

Abstract

The network-level infrastructure management problem involves selecting and scheduling Maintenance, Repair, and Rehabilitation (MR&R) activities on networks of infrastructure facilities so as to maintain the level of service provided by the network in a cost-effective manner. This problem is frequently formulated as a Markov Decision Problem (MDP) solved via Linear Programming (LP). The conditions of facilities are represented by elements of discrete condition rating sets, and transition probabilities are employed to describe deterioration processes. Epistemic and parametric uncertainties not considered within the standard MDP/LP framework are associated with the transition probabilities used in infrastructure management optimization routines. This paper contrasts the expected costs incurred when model uncertainty is ignored with those incurred when this uncertainty is explicitly considered using Robust Optimization. A case study involving a network-level pavement management MDP/LP problem demonstrates how explicitly considering uncertainty may limit worst case MR&R expenditures. The methods and results can also be used to identify the costs of uncertainty in transition probability matrices used in infrastructure management systems.

Suggested Citation

  • 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.
    • Handle: RePEc:cdl:uctcwp:qt6c84b9b4
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/6c84b9b4.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    2. ,, 2004. "Problems And Solutions," Econometric Theory, Cambridge University Press, vol. 20(2), pages 427-429, April.
    3. ,, 2004. "Problems And Solutions," Econometric Theory, Cambridge University Press, vol. 20(1), pages 223-229, February.
    4. 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.
    5. 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.
    6. Kuhn, Kenneth D. & Madanat, Samer M., 2005. "Robust Maintenance Policies in Asset Management," University of California Transportation Center, Working Papers qt00z6g3pr, University of California Transportation Center.
    7. ,, 2000. "Problems And Solutions," Econometric Theory, Cambridge University Press, vol. 16(2), pages 287-299, April.
    8. 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.
    9. Kamal Golabi & Ram B. Kulkarni & George B. Way, 1982. "A Statewide Pavement Management System," Interfaces, INFORMS, vol. 12(6), pages 5-21, December.
    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. Sathaye, Nakul & Madanat, Samer, 2011. "A bottom-up solution for the multi-facility optimal pavement resurfacing problem," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 1004-1017, August.
    2. 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.
    3. Shi, Yue & Xiang, Yisha & Xiao, Hui & Xing, Liudong, 2021. "Joint optimization of budget allocation and maintenance planning of multi-facility transportation infrastructure systems," European Journal of Operational Research, Elsevier, vol. 288(2), pages 382-393.
    4. 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.
    5. Xinhua Mao & Changwei Yuan & Jiahua Gan, 2019. "Incorporating Dynamic Traffic Distribution into Pavement Maintenance Optimization Model," Sustainability, MDPI, vol. 11(9), pages 1-15, April.
    6. Andriotis, C.P. & Papakonstantinou, K.G., 2019. "Managing engineering systems with large state and action spaces through deep reinforcement learning," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    7. 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.
    8. 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.
    9. Sathaye, Nakul & Madanat, Samer, 2012. "A bottom-up optimal pavement resurfacing solution approach for large-scale networks," Transportation Research Part B: Methodological, Elsevier, vol. 46(4), pages 520-528.
    10. 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.
    11. 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.

    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. Donya Rahmani & Arash Zandi & Sara Behdad & Arezou Entezaminia, 2021. "A light robust model for aggregate production planning with consideration of environmental impacts of machines," Operational Research, Springer, vol. 21(1), pages 273-297, March.
    2. Antonio G. Martín & Manuel Díaz-Madroñero & Josefa Mula, 2020. "Master production schedule using robust optimization approaches in an automobile second-tier supplier," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(1), pages 143-166, March.
    3. Wong, Patricia J.Y., 2015. "Eigenvalues of a general class of boundary value problem with derivative-dependent nonlinearity," Applied Mathematics and Computation, Elsevier, vol. 259(C), pages 908-930.
    4. Hanks, Robert W. & Weir, Jeffery D. & Lunday, Brian J., 2017. "Robust goal programming using different robustness echelons via norm-based and ellipsoidal uncertainty sets," European Journal of Operational Research, Elsevier, vol. 262(2), pages 636-646.
    5. Mohsen Jalalimajidi & SM Seyedhosseini & Ahmad Makui & Masoud Babakhani, 2018. "Developing a comprehensive model for new energy replacement in the country’s development program using a robust optimization approach," Energy & Environment, , vol. 29(6), pages 868-890, September.
    6. Mavrotas, George & Figueira, José Rui & Siskos, Eleftherios, 2015. "Robustness analysis methodology for multi-objective combinatorial optimization problems and application to project selection," Omega, Elsevier, vol. 52(C), pages 142-155.
    7. Syam, Muhammed I. & Khashan, Hani A. & Al-Mdallal, Qasem M., 2008. "Nonlinear eigenvalue problems with symmetry," Chaos, Solitons & Fractals, Elsevier, vol. 35(5), pages 931-941.
    8. Zakiyyah, Varachia, 2019. "Overview of Current Trends and Future Directions of Forced Migration," MPRA Paper 106457, University Library of Munich, Germany, revised 2019.
    9. Tao Yao & Supreet Mandala & Byung Chung, 2009. "Evacuation Transportation Planning Under Uncertainty: A Robust Optimization Approach," Networks and Spatial Economics, Springer, vol. 9(2), pages 171-189, June.
    10. Cleber D. Rocco & Reinaldo Morabito, 2016. "Robust optimisation approach applied to the analysis of production / logistics and crop planning in the tomato processing industry," International Journal of Production Research, Taylor & Francis Journals, vol. 54(19), pages 5842-5861, October.
    11. Henao, César Augusto & Ferrer, Juan Carlos & Muñoz, Juan Carlos & Vera, Jorge, 2016. "Multiskilling with closed chains in a service industry: A robust optimization approach," International Journal of Production Economics, Elsevier, vol. 179(C), pages 166-178.
    12. Marla, Lavanya & Rikun, Alexander & Stauffer, Gautier & Pratsini, Eleni, 2020. "Robust modeling and planning: Insights from three industrial applications," Operations Research Perspectives, Elsevier, vol. 7(C).
    13. Jan Kwakkel & Marjolijn Haasnoot & Warren Walker, 2015. "Developing dynamic adaptive policy pathways: a computer-assisted approach for developing adaptive strategies for a deeply uncertain world," Climatic Change, Springer, vol. 132(3), pages 373-386, October.
    14. Shiva Zokaee & Armin Jabbarzadeh & Behnam Fahimnia & Seyed Jafar Sadjadi, 2017. "Robust supply chain network design: an optimization model with real world application," Annals of Operations Research, Springer, vol. 257(1), pages 15-44, October.
    15. Ghazaleh Ahmadi & Reza Tavakkoli-Moghaddam & Armand Baboli & Mehdi Najafi, 2022. "A decision support model for robust allocation and routing of search and rescue resources after earthquake: a case study," Operational Research, Springer, vol. 22(2), pages 1039-1081, April.
    16. Ehsan Pourhadi & Reza Saadati & Sotiris K. Ntouyas, 2019. "Application of Fixed-Point Theory for a Nonlinear Fractional Three-Point Boundary-Value Problem," Mathematics, MDPI, vol. 7(6), pages 1-11, June.
    17. Almaraj, Ismail I. & Trafalis, Theodore B., 2019. "An integrated multi-echelon robust closed- loop supply chain under imperfect quality production," International Journal of Production Economics, Elsevier, vol. 218(C), pages 212-227.
    18. Emmanuel Kwasi Mensah, 2020. "Robust data envelopment analysis via ellipsoidal uncertainty sets with application to the Italian banking industry," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 43(2), pages 491-518, December.
    19. Claudianor O. Alves & Tuhina Mukherjee, 2021. "Existence of solution for a class of elliptic problems in exterior domain with discontinuous nonlinearity," Partial Differential Equations and Applications, Springer, vol. 2(1), pages 1-32, February.
    20. Mohammaddust, Faeghe & Rezapour, Shabnam & Farahani, Reza Zanjirani & Mofidfar, Mohammad & Hill, Alex, 2017. "Developing lean and responsive supply chains: A robust model for alternative risk mitigation strategies in supply chain designs," International Journal of Production Economics, Elsevier, vol. 183(PC), pages 632-653.

    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:qt6c84b9b4. 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.