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An arc-search $${\mathcal {O}}(nL)$$ infeasible-interior-point algorithm for linear programming
Authors:Yaguang Yang  Makoto Yamashita
Institution:1.US NRC, Office of Research,Rockville,USA;2.Department of Mathematical and Computing Science,Tokyo Institute of Technology,Tokyo,Japan
Abstract:Arc-search interior-point methods have been proposed to capture the curvature of the central path using an approximation based on ellipse. Yang et al. (J Appl Math Comput 51(1–2):209–225, 2016) proved that an arc-search algorithm has the computational order of \({\mathcal {O}}(n^{5/4}L)\). In this paper, we propose an arc-search infeasible-interior-point algorithms and discuss its convergence analysis. We improve the polynomial bound from \({\mathcal {O}}(n^{5/4}L)\) to \({\mathcal {O}}(nL)\), which is at least as good as the best existing bound for infeasible-interior-point algorithms for linear programming. Numerical results indicate that the proposed method solved LP instances faster than the existing \({\mathcal {O}}(n^{5/4}L)\) method.
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