| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 4642063 | Journal of Computational and Applied Mathematics | 2008 | 14 Pages |
Abstract
In this paper, the feasible type SQP method is improved. A new SQP algorithm is presented to solve the nonlinear inequality constrained optimization. As compared with the existing SQP methods, per single iteration, in order to obtain the search direction, it is only necessary to solve equality constrained quadratic programming subproblems and systems of linear equations. Under some suitable conditions, the global and superlinear convergence can be induced.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Zhibin Zhu,