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A self-concordance property for nonconvex semidefinite programming

Author

Listed:
  • Rodrigo Garcés
  • Walter Gómez
  • Florian Jarre

Abstract

The paper considers nonconvex quadratic semidefinite problems. This class arises, for instance, as subproblems in the sequential semidefinite programming algorithm for solving general smooth nonlinear semidefinite problems. We extend locally the concept of self-concordance to problems that satisfy a weak version of the second order sufficient optimality conditions. Copyright Springer-Verlag 2011

Suggested Citation

  • 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.
    • Handle: RePEc:spr:mathme:v:74:y:2011:i:1:p:77-92
    DOI: 10.1007/s00186-011-0350-9
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    References listed on IDEAS

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    1. F. Leibfritz & J. Maruhn, 2009. "A successive SDP-NSDP approach to a robust optimization problem in finance," Computational Optimization and Applications, Springer, vol. 44(3), pages 443-466, December.
    2. 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.
    3. Anand, C. & Sotirov, R. & Terlaky, T. & Zheng, Z., 2007. "Magnetic resonance tissue density estimation using optimal SSFP pulse-sequence design," Other publications TiSEM 371b5075-1085-4bf5-bd55-4, Tilburg University, School of Economics and Management.
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