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Abstract
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In this paper, we present a corrector–predictor path-following interior-point method for second-order cone
optimization (SOCO) based on a new proximity measure. The algorithm produces a sequence of iterates
in a neighbourhood of the central path based on a new proximity measure. We show that the algorithm
is well-defined and derive the complexity bound for the algorithm. We obtain the best-known result for
SOCO. The numerical results show that the proposed algorithm is effective.
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