IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v95y2010i5p499-510.html
   My bibliography  Save this article

On buffered failure probability in design and optimization of structures

Author

Listed:
  • Rockafellar, R.T.
  • Royset, J.O.

Abstract

In reliability engineering focused on the design and optimization of structures, the typical measure of reliability is the probability of failure of the structure or its individual components relative to specific limit states. However, the failure probability has troublesome properties that raise several theoretical, practical, and computational issues. This paper explains the seriousness of these issues in the context of design optimization and goes on to propose a new alternative measure, the buffered failure probability, which offers significant advantages. The buffered failure probability is handled with relative ease in design optimization problems, accounts for the degree of violation of a performance threshold, and is more conservative than the failure probability.

Suggested Citation

  • Rockafellar, R.T. & Royset, J.O., 2010. "On buffered failure probability in design and optimization of structures," Reliability Engineering and System Safety, Elsevier, vol. 95(5), pages 499-510.
  • Handle: RePEc:eee:reensy:v:95:y:2010:i:5:p:499-510
    DOI: 10.1016/j.ress.2010.01.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832010000177
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2010.01.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. J. O. Royset & E. Polak, 2004. "Implementable Algorithm for Stochastic Optimization Using Sample Average Approximations," Journal of Optimization Theory and Applications, Springer, vol. 122(1), pages 157-184, July.
    2. Kurt Marti, 2005. "Stochastic Optimization Methods," Springer Books, Springer, number 978-3-540-26848-2, September.
    3. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
    4. E. Polak & J. O. Royset & R. S. Womersley, 2003. "Algorithms with Adaptive Smoothing for Finite Minimax Problems," Journal of Optimization Theory and Applications, Springer, vol. 119(3), pages 459-484, December.
    5. J. O. Royset & E. Polak, 2007. "Extensions of Stochastic Optimization Results to Problems with System Failure Probability Functions," Journal of Optimization Theory and Applications, Springer, vol. 133(1), pages 1-18, April.
    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. Massimiliano Amarante, 2016. "A representation of risk measures," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 39(1), pages 95-103, April.
    2. Abate, Arega Getaneh & Riccardi, Rossana & Ruiz, Carlos, 2021. "Contracts in electricity markets under EU ETS: A stochastic programming approach," Energy Economics, Elsevier, vol. 99(C).
    3. Chang, Kuo-Hao & Cuckler, Robert & Lee, Song-Lin & Lee, Loo Hay, 2022. "Discrete conditional-expectation-based simulation optimization: Methodology and applications," European Journal of Operational Research, Elsevier, vol. 298(1), pages 213-228.
    4. Jakeman, John D. & Kouri, Drew P. & Huerta, J. Gabriel, 2022. "Surrogate modeling for efficiently, accurately and conservatively estimating measures of risk," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    5. Byun, Ji-Eun & de Oliveira, Welington & Royset, Johannes O., 2023. "S-BORM: Reliability-based optimization of general systems using buffered optimization and reliability method," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    6. L. Jeff Hong & Zhaolin Hu & Liwei Zhang, 2014. "Conditional Value-at-Risk Approximation to Value-at-Risk Constrained Programs: A Remedy via Monte Carlo," INFORMS Journal on Computing, INFORMS, vol. 26(2), pages 385-400, May.
    7. Justin R. Davis & Stan Uryasev, 2016. "Analysis of tropical storm damage using buffered probability of exceedance," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(1), pages 465-483, August.
    8. Alcántara Mata, Antonio & Ruiz Mora, Carlos, 2022. "On data-driven chance constraint learning for mixed-integer optimization problems," DES - Working Papers. Statistics and Econometrics. WS 35425, Universidad Carlos III de Madrid. Departamento de Estadística.
    9. Danjue Shang & Victor Kuzmenko & Stan Uryasev, 2018. "Cash flow matching with risks controlled by buffered probability of exceedance and conditional value-at-risk," Annals of Operations Research, Springer, vol. 260(1), pages 501-514, January.
    10. Guo, Tiexin & Wang, Hongji & Li, Jinglai & Wang, Hongqiao, 2024. "Sampling-based adaptive design strategy for failure probability estimation," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    11. Chaudhuri, Anirban & Kramer, Boris & Willcox, Karen E., 2020. "Information Reuse for Importance Sampling in Reliability-Based Design Optimization," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    12. Villanueva, D. & Haftka, R.T. & Sankar, B.V., 2014. "Accounting for future redesign to balance performance and development costs," Reliability Engineering and System Safety, Elsevier, vol. 124(C), pages 56-67.
    13. Mafusalov, Alexander & Uryasev, Stan, 2016. "CVaR (superquantile) norm: Stochastic case," European Journal of Operational Research, Elsevier, vol. 249(1), pages 200-208.
    14. Tan, Caixia & Wang, Jing & Geng, Shiping & Pu, Lei & Tan, Zhongfu, 2021. "Three-level market optimization model of virtual power plant with carbon capture equipment considering copula–CVaR theory," Energy, Elsevier, vol. 237(C).
    15. Xiaojiao Tong & Hailin Sun & Xiao Luo & Quanguo Zheng, 2018. "Distributionally robust chance constrained optimization for economic dispatch in renewable energy integrated systems," Journal of Global Optimization, Springer, vol. 70(1), pages 131-158, January.
    16. Rockafellar, R.T. & Royset, J.O. & Miranda, S.I., 2014. "Superquantile regression with applications to buffered reliability, uncertainty quantification, and conditional value-at-risk," European Journal of Operational Research, Elsevier, vol. 234(1), pages 140-154.
    17. Mikhail Zhitlukhin, 2018. "Monotone Sharpe ratios and related measures of investment performance," Papers 1809.10193, arXiv.org, revised May 2021.
    18. Rocchetta, Roberto & Crespo, Luis G., 2021. "A scenario optimization approach to reliability-based and risk-based design: Soft-constrained modulation of failure probability bounds," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    19. Amarjit Budhiraja & Shu Lu & Yang Yu & Quoc Tran-Dinh, 2021. "Minimization of a class of rare event probabilities and buffered probabilities of exceedance," Annals of Operations Research, Springer, vol. 302(1), pages 49-83, July.
    20. Pertaia, Giorgi & Prokhorov, Artem & Uryasev, Stan, 2022. "A new approach to credit ratings," Journal of Banking & Finance, Elsevier, vol. 140(C).
    21. Matthew Norton & Valentyn Khokhlov & Stan Uryasev, 2021. "Calculating CVaR and bPOE for common probability distributions with application to portfolio optimization and density estimation," Annals of Operations Research, Springer, vol. 299(1), pages 1281-1315, April.
    22. Thilini V. Mahanama & Abootaleb Shirvani & Svetlozar Rachev, 2023. "The Financial Market of Indices of Socioeconomic Wellbeing," Papers 2303.05654, arXiv.org.
    23. R. Tyrrell Rockafellar & Johannes O. Royset, 2018. "Superquantile/CVaR risk measures: second-order theory," Annals of Operations Research, Springer, vol. 262(1), pages 3-28, March.
    24. Franco Peschiera & Robert Dell & Johannes Royset & Alain Haït & Nicolas Dupin & Olga Battaïa, 2021. "A novel solution approach with ML-based pseudo-cuts for the Flight and Maintenance Planning problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(3), pages 635-664, September.
    25. Johannes O. Royset & Roberto Szechtman, 2013. "Optimal Budget Allocation for Sample Average Approximation," Operations Research, INFORMS, vol. 61(3), pages 762-776, June.

    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. Johannes Royset, 2013. "On sample size control in sample average approximations for solving smooth stochastic programs," Computational Optimization and Applications, Springer, vol. 55(2), pages 265-309, June.
    2. Wim Ackooij & Pedro Pérez-Aros, 2020. "Gradient Formulae for Nonlinear Probabilistic Constraints with Non-convex Quadratic Forms," Journal of Optimization Theory and Applications, Springer, vol. 185(1), pages 239-269, April.
    3. Lukáš Adam & Martin Branda & Holger Heitsch & René Henrion, 2020. "Solving joint chance constrained problems using regularization and Benders’ decomposition," Annals of Operations Research, Springer, vol. 292(2), pages 683-709, September.
    4. J. O. Royset & E. Polak, 2007. "Extensions of Stochastic Optimization Results to Problems with System Failure Probability Functions," Journal of Optimization Theory and Applications, Springer, vol. 133(1), pages 1-18, April.
    5. Cui, Xueting & Zhu, Shushang & Sun, Xiaoling & Li, Duan, 2013. "Nonlinear portfolio selection using approximate parametric Value-at-Risk," Journal of Banking & Finance, Elsevier, vol. 37(6), pages 2124-2139.
    6. Zhi Chen & Melvyn Sim & Huan Xu, 2019. "Distributionally Robust Optimization with Infinitely Constrained Ambiguity Sets," Operations Research, INFORMS, vol. 67(5), pages 1328-1344, September.
    7. Dominique Guégan & Wayne Tarrant, 2012. "On the necessity of five risk measures," Annals of Finance, Springer, vol. 8(4), pages 533-552, November.
    8. Giovanni Masala & Filippo Petroni, 2023. "Drawdown risk measures for asset portfolios with high frequency data," Annals of Finance, Springer, vol. 19(2), pages 265-289, June.
    9. Ke Zhou & Jiangjun Gao & Duan Li & Xiangyu Cui, 2017. "Dynamic mean–VaR portfolio selection in continuous time," Quantitative Finance, Taylor & Francis Journals, vol. 17(10), pages 1631-1643, October.
    10. Malavasi, Matteo & Ortobelli Lozza, Sergio & Trück, Stefan, 2021. "Second order of stochastic dominance efficiency vs mean variance efficiency," European Journal of Operational Research, Elsevier, vol. 290(3), pages 1192-1206.
    11. Rostagno, Luciano Martin, 2005. "Empirical tests of parametric and non-parametric Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) measures for the Brazilian stock market index," ISU General Staff Papers 2005010108000021878, Iowa State University, Department of Economics.
    12. Alois Pichler, 2013. "Premiums And Reserves, Adjusted By Distortions," Papers 1304.0490, arXiv.org.
    13. Alexander, Gordon J. & Baptista, Alexandre M. & Yan, Shu, 2013. "A comparison of the original and revised Basel market risk frameworks for regulating bank capital," Journal of Economic Behavior & Organization, Elsevier, vol. 85(C), pages 249-268.
    14. Benjamin Lev, 2005. "Book Reviews," Interfaces, INFORMS, vol. 35(5), pages 436-444, October.
    15. Li, Bo & Hou, Peng-Wen & Chen, Ping & Li, Qing-Hua, 2016. "Pricing strategy and coordination in a dual channel supply chain with a risk-averse retailer," International Journal of Production Economics, Elsevier, vol. 178(C), pages 154-168.
    16. Jin, Xin & Zhang, Zhaolong & Shi, Xiaoqiang & Ju, Wenbin, 2014. "A review on wind power industry and corresponding insurance market in China: Current status and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 1069-1082.
    17. Alexander, Gordon J. & Baptista, Alexandre M. & Yan, Shu, 2012. "When more is less: Using multiple constraints to reduce tail risk," Journal of Banking & Finance, Elsevier, vol. 36(10), pages 2693-2716.
    18. Kull, Andreas, 2009. "Sharing Risk – An Economic Perspective," ASTIN Bulletin, Cambridge University Press, vol. 39(2), pages 591-613, November.
    19. Mínguez, R. & Conejo, A.J. & García-Bertrand, R., 2011. "Reliability and decomposition techniques to solve certain class of stochastic programming problems," Reliability Engineering and System Safety, Elsevier, vol. 96(2), pages 314-323.
    20. Fattahi, Mohammad & Keyvanshokooh, Esmaeil & Kannan, Devika & Govindan, Kannan, 2023. "Resource planning strategies for healthcare systems during a pandemic," European Journal of Operational Research, Elsevier, vol. 304(1), pages 192-206.

    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:eee:reensy:v:95:y:2010:i:5:p:499-510. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    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.