Primal-dual interior point methods in linear, quadratic and semidefinite programming problems
Автор: Kulagin N.A., Bulyakova I.A.
Журнал: Сетевое научное издание «Системный анализ в науке и образовании» @journal-sanse
Статья в выпуске: 4, 2023 года.
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In this paper we consider three classes of convex optimization problems - linear, quadratic and semidefinite programming problems, then we derive and analyze a «predictor-corrector» interior point algorithm for each class of problems. Finally, we conduct numerical experiments to verify theoretical results.
Primal-dual interior point methods, ipm, numerical optimization, convex optimization, dual problem, newton's method, karush-kuhn-tucker conditions
Короткий адрес: https://sciup.org/14129821
IDR: 14129821
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