An arc-search infeasible-interior-point method for symmetric optimization in a wide neighborhood of the central path

التفاصيل البيبلوغرافية
العنوان: An arc-search infeasible-interior-point method for symmetric optimization in a wide neighborhood of the central path
المؤلفون: Yinkui Zhang, Ximei Yang, Hongwei Liu
المصدر: Optimization Letters. 11:135-152
بيانات النشر: Springer Science and Business Media LLC, 2016.
سنة النشر: 2016
مصطلحات موضوعية: Discrete mathematics, 021103 operations research, Control and Optimization, Jordan algebra, Rank (linear algebra), 0211 other engineering and technologies, 010103 numerical & computational mathematics, 02 engineering and technology, Ellipse, 01 natural sciences, Combinatorics, Path (graph theory), Euclidean geometry, Convergence (routing), 0101 mathematics, Commutative property, Interior point method, Mathematics
الوصف: In this paper, we propose a new arc-search infeasible-interior-point method for symmetric optimization using a wide neighborhood of the central path. The proposed algorithm searches for optimizers along the ellipses that approximate the central path. The convergence is shown for a commutative class of search directions, which includes the Nesterov–Todd direction and the xs and sx directions. The complexity bound is $$\mathcal {O}(r^{5/4}\log \varepsilon ^{-1})$$ for the Nesterov–Todd direction, and $$\mathcal {O}(r^{7/4}\log \varepsilon ^{-1})$$ for the xs and sx directions, where r is the rank of the associated Euclidean Jordan algebra and $$\varepsilon $$ is the required precision. The obtained complexity bounds coincide with the currently best known theoretical complexity bounds for the short step path-following algorithm. Some limited encouraging computational results are reported.
تدمد: 1862-4480
1862-4472
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::1d6aa1b26947852d32e1608bd26af4c5
https://doi.org/10.1007/s11590-016-0997-5
حقوق: CLOSED
رقم الأكسشن: edsair.doi...........1d6aa1b26947852d32e1608bd26af4c5
قاعدة البيانات: OpenAIRE