Volumetric barrier decomposition algorithms for stochastic quadratic second-order cone programming

Baha Alzalg

Applied Mathematics and Computation, 2015, vol. 265, issue C, 494-508

Abstract: Ariyawansa and Zhu (2011) have derived volumetric barrier decomposition algorithms for solving two-stage stochastic semidefinite programs and proved polynomial complexity of certain members of the algorithms. In this paper, we utilize their work to derive volumetric barrier decomposition algorithms for solving two-stage stochastic convex quadratic second-order cone programming, and establish polynomial complexity of certain members of the proposed algorithms.

Keywords: Quadratic second-order cone programming; Stochastic programming; Interior point methods; Volumetric barrier; Self-concordance (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:265:y:2015:i:c:p:494-508

DOI: 10.1016/j.amc.2015.05.014

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