Subspace-stabilized sequential quadratic programming

The stabilized sequential quadratic programming (SQP) method has nice local convergence properties: it possesses local superlinear convergence under very mild assumptions not including any constraint qualifications. However, any attempts to globalize convergence of this method indispensably face some principal difficulties concerned with intrinsic deficiencies of the steps produced by it when relatively far from solutions; specifically, it has a tendency to produce long sequences of short steps before entering the region where its superlinear convergence shows up. In this paper, we propose a modification of the stabilized SQP method, possessing better “semi-local” behavior, and hence, more suitable for the development of practical realizations. The key features of the new method are identification of the so-called degeneracy subspace and dual stabilization along this subspace only; thus the name “subspace-stabilized SQP”. We consider two versions of this method, their local convergence properties, as well as a practical procedure for approximation of the degeneracy subspace. Even though we do not consider here any specific algorithms with theoretically justified global convergence properties, subspace-stabilized SQP can be a relevant substitute for the stabilized SQP in such algorithms using the latter at the “local phase”. Some numerical results demonstrate that stabilization along the degeneracy subspace is indeed crucially important for success of dual stabilization methods. © 2017, Springer Science+Business Media New York.

Авторы
Izmailov A.F. 1, 2 , Uskov E.I.3
Издательство
Springer New York LLC
Номер выпуска
1
Язык
Английский
Страницы
129-154
Статус
Опубликовано
Том
67
Год
2017
Организации
  • 1 OR Department, VMK Faculty, Lomonosov Moscow State University, MSU, Uchebniy Korpus 2, Leninskiye Gory, Moscow, 119991, Russian Federation
  • 2 RUDN University, Miklukho-Maklaya Str. 6, Moscow, 117198, Russian Federation
  • 3 Department of Mathematic, Physics and Computer Sciences, Derzhavin Tambov State University, TSU, Internationalnaya 33, Tambov, 392000, Russian Federation
Ключевые слова
Degenerate solution; Dual stabilization; Global convergence; Noncritical Lagrange multiplier; Sequential quadratic programming; Superlinear convergence
Дата создания
19.10.2018
Дата изменения
19.10.2018
Постоянная ссылка
https://repository.rudn.ru/ru/records/article/record/5526/