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An SQP-type algorithm for nonlinear second-order cone programs

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Abstract

We propose an SQP-type algorithm for solving nonlinear second-order cone programming (NSOCP) problems. At every iteration, the algorithm solves a convex SOCP subproblem in which the constraints involve linear approximations of the constraint functions in the original problem and the objective function is a convex quadratic function. Those subproblems can be transformed into linear SOCP problems, for which efficient interior point solvers are available. We establish global convergence and local quadratic convergence of the algorithm under appropriate assumptions. We report numerical results to examine the effectiveness of the algorithm.

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Authors and Affiliations

  1. Department of Applied Mathematics and Physics, Graduate School of Informatics, Kyoto University, Kyoto, 606-8501, Japan

    Hirokazu Kato & Masao Fukushima

Authors
  1. Hirokazu Kato
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  2. Masao Fukushima
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Correspondence to Masao Fukushima.

Additional information

This work was supported in part by the Scientific Research Grant-in-Aid from Japan Society for the Promotion of Science.

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Kato, H., Fukushima, M. An SQP-type algorithm for nonlinear second-order cone programs. Optimization Letters 1, 129–144 (2007). https://doi.org/10.1007/s11590-006-0009-2

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  • DOI: https://doi.org/10.1007/s11590-006-0009-2

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