Combining stabilized SQP with the augmented Lagrangian algorithm

Izmailov, A.F.; Solodov, M.V.; Uskov, E.I.

Статья опубликована в высокорейтинговом журнале

Информация о цитировании статьи получена из Web of Science, Scopus
Статья опубликована в журнале из списка Web of Science и/или Scopus
Дата последнего поиска статьи во внешних источниках: 13 ноября 2015 г.

Авторы: Izmailov A.F., Solodov M.V., Uskov E.I.
Журнал: Computational Optimization and Applications
Том: 62
Номер: 2
Год издания: 2015
Издательство: Springer Nature
Местоположение издательства: Switzerland
Первая страница: 405
Последняя страница: 429
DOI: 10.1007/s10589-015-9744-6
Аннотация: For an optimization problem with general equality and inequality constraints, we propose an algorithm which uses subproblems of the stabilized SQP (sSQP) type for approximately solving subproblems of the augmented Lagrangian method. The motivation is to take advantage of the well-known robust behavior of the augmented Lagrangian algorithm, including on problems with degenerate constraints, and at the same time try to reduce the overall algorithm locally to sSQP (which gives fast local convergence rate under weak assumptions). Specifically, the algorithm first verifies whether the primal-dual sSQP step (with unit stepsize) makes good progress towards decreasing the violation of optimality conditions for the original problem, and if so, makes this step. Otherwise, the primal part of the sSQP direction is used for linesearch that decreases the augmented Lagrangian, keeping the multiplier estimate fixed for the time being. The overall algorithm has reasonable global convergence guarantees, and inherits strong local convergence rate properties of sSQP under the same weak assumptions. Numerical results on degenerate problems and comparisons with some alternatives are reported.
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