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Abstract
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Abstract: In this paper, we present a second-order corrector infeasible interior-point
method for linear optimization in a large neighborhood of the central path. The in-
novation of our method is to calculate the predictor directions using a speci c kernel
function instead of the logarithmic barrier function. We decompose the predictor direc-
tion induced by the kernel function to two orthogonal directions of the corresponding
to the negative and positive component of the right-hand side vector of the centering
equation. The method then considers the new point as a linear combination of these
directions along with a second-order corrector direction. The convergence analysis of
the proposed method is investigated and it is proved that the complexity bound is
O(n
5
4 log "1).
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