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    A new full Nesterov-Todd step feasible interior-point method for convex quadratic symmetric cone optimization

    Access Status
    Fulltext not available
    Authors
    Wang, G.
    Yu, C.
    Teo, Kok Lay
    Date
    2013
    Type
    Journal Article
    
    Metadata
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    Citation
    Wang, G.Q. and Yu, C.J. and Teo, K.L. 2013. A new full Nesterov-Todd step feasible interior-point method for convex quadratic symmetric cone optimization. Applied Mathematics and Computations. 221: pp. 329-343.
    Source Title
    Applied Mathematics and Computations
    DOI
    10.1016/j.amc.2013.06.064
    ISSN
    0096-3003
    URI
    http://hdl.handle.net/20.500.11937/34134
    Collection
    • Curtin Research Publications
    Abstract

    In this paper, we generalize the classical primal–dual logarithmic barrier method for linear optimization to convex quadratic optimization over symmetric cone by using Euclidean Jordan algebras. The symmetrization of the search directions used in this paper is based on the Nesterov–Todd scaling scheme, and only full Nesterov–Todd step is used at each iteration. We derive the iteration bound that matches the currently best known iteration bound for small-update methods, namely, O(√rlog4/ε. Some preliminary numerical results are provided to demonstrate the computational performance of the proposed algorithm.

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