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Sequential Semidefinite Program for Maximum Robustness Design of Structures under Load Uncertainty

Author

Listed:
  • Y. Kanno

    (The University of Tokyo)

  • I. Takewaki

    (Kyoto University)

Abstract

A robust structural optimization scheme as well as an optimization algorithm are presented based on the robustness function. Under the uncertainties of the external forces based on the info-gap model, the maximization of the robustness function is formulated as an optimization problem with infinitely many constraints. By using the quadratic embedding technique of uncertainty and the S-procedure, we reformulate the problem into a nonlinear semidefinite programming problem. A sequential semidefinite programming method is proposed which has a global convergent property. It is shown through numerical examples that optimum designs of various linear elastic structures can be found without difficulty.

Suggested Citation

  • Y. Kanno & I. Takewaki, 2006. "Sequential Semidefinite Program for Maximum Robustness Design of Structures under Load Uncertainty," Journal of Optimization Theory and Applications, Springer, vol. 130(2), pages 265-287, August.
    • Handle: RePEc:spr:joptap:v:130:y:2006:i:2:d:10.1007_s10957-006-9102-z
    DOI: 10.1007/s10957-006-9102-z
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    Cited by:

    1. Rodrigo Garcés & Walter Gómez & Florian Jarre, 2011. "A self-concordance property for nonconvex semidefinite programming," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 74(1), pages 77-92, August.
    2. Qi Zhao & Zhongwen Chen, 2018. "An SQP-type Method with Superlinear Convergence for Nonlinear Semidefinite Programming," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 35(03), pages 1-25, June.

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