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Homogeneous Self-dual Algorithms for Stochastic Second-Order Cone Programming

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  • Baha Alzalg

    (The University of Jordan)

Abstract

Jin et al. (in J. Optim. Theory Appl. 155:1073–1083, 2012) proposed homogeneous self-dual algorithms for stochastic semidefinite programs with finite event space. In this paper, we utilize their work to derive homogeneous self-dual algorithms for stochastic second-order cone programs with finite event space. We also show how the structure in the stochastic second-order cone programming problems may be exploited so that the algorithms developed for these problems have less complexity than the algorithms developed for stochastic semidefinite programs mentioned above.

Suggested Citation

  • Baha Alzalg, 2014. "Homogeneous Self-dual Algorithms for Stochastic Second-Order Cone Programming," Journal of Optimization Theory and Applications, Springer, vol. 163(1), pages 148-164, October.
    • Handle: RePEc:spr:joptap:v:163:y:2014:i:1:d:10.1007_s10957-013-0428-z
    DOI: 10.1007/s10957-013-0428-z
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    References listed on IDEAS

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    1. Yu. E. Nesterov & M. J. Todd, 1997. "Self-Scaled Barriers and Interior-Point Methods for Convex Programming," Mathematics of Operations Research, INFORMS, vol. 22(1), pages 1-42, February.
    2. S. Jin & K. A. Ariyawansa & Y. Zhu, 2012. "Homogeneous Self-dual Algorithms for Stochastic Semidefinite Programming," Journal of Optimization Theory and Applications, Springer, vol. 155(3), pages 1073-1083, December.
    3. F. Maggioni & F. A. Potra & M. I. Bertocchi & E. Allevi, 2009. "Stochastic Second-Order Cone Programming in Mobile Ad Hoc Networks," Journal of Optimization Theory and Applications, Springer, vol. 143(2), pages 309-328, November.
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    Cited by:

    1. Baha Alzalg & Khaled Badarneh & Ayat Ababneh, 2019. "An Infeasible Interior-Point Algorithm for Stochastic Second-Order Cone Optimization," Journal of Optimization Theory and Applications, Springer, vol. 181(1), pages 324-346, April.
    2. Baha Alzalg, 2019. "A primal-dual interior-point method based on various selections of displacement step for symmetric optimization," Computational Optimization and Applications, Springer, vol. 72(2), pages 363-390, March.

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