A nonmonotone filter method for nonlinear optimization
We propose a new nonmonotone filter method to promote global and fast local convergence for sequential quadratic programming algorithms. Our method uses two filters: a standard, global g-filter for global convergence, and a local nonmonotone l-filter that allows us to establish fast local convergence. We show how to switch between the two filters efficiently, and we prove global and superlinear local convergence. A special feature of the proposed method is that it does not require second-order correction steps. We present preliminary numerical results comparing our implementation with a classical filter SQP method. Copyright Springer Science+Business Media, LLC 2012
Volume (Year): 52 (2012)
Issue (Month): 3 (July)
|Contact details of provider:|| Web page: http://www.springer.com/math/journal/10589 |
|Order Information:||Web: http://link.springer.de/orders.htm|
When requesting a correction, please mention this item's handle: RePEc:spr:coopap:v:52:y:2012:i:3:p:583-607. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Guenther Eichhorn)or (Christopher F Baum)
If references are entirely missing, you can add them using this form.