| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1704845 | Applied Mathematical Modelling | 2012 | 11 Pages |
Abstract
A new sequential quadratic programming (SQP) method for nonlinear inequality constrained optimization is proposed. The aim of this paper is to promote global convergence for SQP methods using a flexible step acceptance strategy which combines merit functions and filter techniques. Global convergence is proved under some reasonable assumptions and preliminary numerical results are reported.
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Authors
Xiaojing Zhu, Dingguo Pu,