IDEAS home Printed from https://ideas.repec.org/a/spr/joptap/v144y2010i1d10.1007_s10957-009-9586-4.html
   My bibliography  Save this article

Multihazard Design: Structural Optimization Approach

Author

Listed:
  • F. A. Potra

    (National Institute of Standards and Technology)

  • E. Simiu

    (National Institute of Standards and Technology)

Abstract

The objective of multihazard structural engineering is to develop methodologies for achieving designs that are safe and cost-effective under multiple hazards. Optimization is a natural tool for achieving such designs. In general, its aim is to determine a vector of design variables subjected to a given set of constraints, such that an objective function of those variables is minimized. In the particular case of structural design, the design variables may be member sizes; the constraints pertain to structural strength and serviceability (e.g., keeping the load-induced stresses and deflections below specified thresholds); and the objective function is the structure cost or weight. In a multihazard context, the design variables are subjected to the constraints imposed by all the hazards to which the structure is exposed. In this paper, we formulate the multihazard structural design problem in nonlinear programming terms and present a simple illustrative example involving four design variables and two hazards: earthquake and strong winds. Results of our numerical experiments show that interior-point methods are significantly more efficient than classical optimization methods in solving the nonlinear programming problem associated with our illustrative example.

Suggested Citation

  • F. A. Potra & E. Simiu, 2010. "Multihazard Design: Structural Optimization Approach," Journal of Optimization Theory and Applications, Springer, vol. 144(1), pages 120-136, January.
    • Handle: RePEc:spr:joptap:v:144:y:2010:i:1:d:10.1007_s10957-009-9586-4
    DOI: 10.1007/s10957-009-9586-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10957-009-9586-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10957-009-9586-4?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. Dimitris Bertsimas & Ioana Popescu, 2002. "On the Relation Between Option and Stock Prices: A Convex Optimization Approach," Operations Research, INFORMS, vol. 50(2), pages 358-374, April.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. Georgia Perakis & Guillaume Roels, 2008. "Regret in the Newsvendor Model with Partial Information," Operations Research, INFORMS, vol. 56(1), pages 188-203, February.
    3. Jarno Talponen, 2013. "Matching distributions: Asset pricing with density shape correction," Papers 1312.4227, arXiv.org, revised Mar 2018.
    4. repec:dau:papers:123456789/30 is not listed on IDEAS
    5. Shane Barratt & Jonathan Tuck & Stephen Boyd, 2020. "Convex Optimization Over Risk-Neutral Probabilities," Papers 2003.02878, arXiv.org.
    6. Roy H. Kwon & Jonathan Y. Li, 2016. "A stochastic semidefinite programming approach for bounds on option pricing under regime switching," Annals of Operations Research, Springer, vol. 237(1), pages 41-75, February.
    7. anonymous, 2006. "The MSOM Society Student Paper Competition: Extended Abstracts of 2005 Winners," Manufacturing & Service Operations Management, INFORMS, vol. 8(1), pages 98-117.
    8. Burer, Samuel & Jones, Philip C. & Lowe, Timothy J., 2008. "Coordinating the supply chain in the agricultural seed industry," European Journal of Operational Research, Elsevier, vol. 185(1), pages 354-377, February.
    9. Liu, Guoqing & Li, Wenbo V., 2009. "Moment bounds for truncated random variables," Statistics & Probability Letters, Elsevier, vol. 79(18), pages 1951-1956, September.
    10. Li Chen & Simai He & Shuzhong Zhang, 2011. "Tight Bounds for Some Risk Measures, with Applications to Robust Portfolio Selection," Operations Research, INFORMS, vol. 59(4), pages 847-865, August.
    11. Arash Fahim & Yu-Jui Huang, 2016. "Model-independent superhedging under portfolio constraints," Finance and Stochastics, Springer, vol. 20(1), pages 51-81, January.
    12. Keith Zorn & Nikolaos Sahinidis, 2014. "Global optimization of general nonconvex problems with intermediate polynomial substructures," Journal of Global Optimization, Springer, vol. 59(2), pages 673-693, July.
    13. Adrian Gepp & Geoff Harris & Bruce Vanstone, 2020. "Financial applications of semidefinite programming: a review and call for interdisciplinary research," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(4), pages 3527-3555, December.
    14. Mathias Beiglbock & Pierre Henry-Labord`ere & Friedrich Penkner, 2011. "Model-independent Bounds for Option Prices: A Mass Transport Approach," Papers 1106.5929, arXiv.org, revised Feb 2013.
    15. Arash Fahim & Yu-Jui Huang, 2014. "Model-independent Superhedging under Portfolio Constraints," Papers 1402.2599, arXiv.org, revised Jun 2015.
    16. Mathias Beiglböck & Pierre Henry-Labordère & Friedrich Penkner, 2013. "Model-independent bounds for option prices—a mass transport approach," Finance and Stochastics, Springer, vol. 17(3), pages 477-501, July.
    17. H. Albrecher & P. A. Mayer & W. Schoutens, 2008. "General Lower Bounds for Arithmetic Asian Option Prices," Applied Mathematical Finance, Taylor & Francis Journals, vol. 15(2), pages 123-149.
    18. Arash Fahim & Yu-Jui Huang, 2016. "Model-independent superhedging under portfolio constraints," Finance and Stochastics, Springer, vol. 20(1), pages 51-81, January.
    19. Roy Kwon & Jonathan Li, 2016. "A stochastic semidefinite programming approach for bounds on option pricing under regime switching," Annals of Operations Research, Springer, vol. 237(1), pages 41-75, February.
    20. Dimitris Bertsimas & Aurélie Thiele, 2006. "A Robust Optimization Approach to Inventory Theory," Operations Research, INFORMS, vol. 54(1), pages 150-168, February.
    21. Tsiaras, Leonidas, 2009. "The Forecast Performance of Competing Implied Volatility Measures: The Case of Individual Stocks," Finance Research Group Working Papers F-2009-02, University of Aarhus, Aarhus School of Business, Department of Business Studies.

    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:spr:joptap:v:144:y:2010:i:1:d:10.1007_s10957-009-9586-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.