首页 | 本学科首页   官方微博 | 高级检索  
     检索      


A nonmonotone filter method for nonlinear optimization
Authors:Chungen Shen  Sven Leyffer  Roger Fletcher
Institution:1. Department of Applied Mathematics, Shanghai Finance University, Shanghai, 201209, China
2. Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, 60439, USA
3. Mathematics Department, University of Dundee, Dundee, UK
Abstract: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.
Keywords:
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号