Year: 1995
Author: Tian-De Guo, Shi-Quan Wu
Journal of Computational Mathematics, Vol. 13 (1995), Iss. 2 : pp. 161–171
Abstract
Predictor-corrector algorithm for linear programming, proposed by Mizuno et al.$^{[1]}$, becomes the best well known in the interior point methods. The purpose of this paper is to extend these results in two directions. First, we modify the algorithm in order to solve convex quadratic programming with upper bounds. Second, we replace the corrector step with an iteration of Monteiro and Adler's algorithm$^{[2]}$. With these modifications, the duality gap is reduced by a constant factor after each corrector step for convex quadratic programming. It is shown that the new algorithm has a $O(\sqrt nL)$-iteration complexity.
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Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/1995-JCM-9259
Journal of Computational Mathematics, Vol. 13 (1995), Iss. 2 : pp. 161–171
Published online: 1995-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 11