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Infeasible interior-point methods for linear optimization based on large neighborhood. (English) Zbl 1346.90567
Summary: In this paper, we design a class of infeasible interior-point methods for linear optimization based on large neighborhood. The algorithm is inspired by a full-Newton step infeasible algorithm with a linear convergence rate in problem dimension that was recently proposed by the second author. Unfortunately, despite its good numerical behavior, the theoretical convergence rate of our algorithm is worse up to square root of problem dimension.

MSC:
90C05 Linear programming
90C51 Interior-point methods
Software:
LIPSOL; LOQO; Mosek; PCx
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