首页 | 本学科首页   官方微博 | 高级检索  
     


Combining search directions using gradient flows
Authors:Javier M. Moguerza  Francisco J. Prieto
Affiliation:(1) School of Engineering, Univ. Rey Juan Carlos, Madrid, Spain, e-mail: j.moguerza@escet.urjc.es. Research supported by Spanish MEC grant TIC2000-1750-C06-04 and CAM project 07T/0005/2001, ES;(2) Dept. of Statistics and Econometrics, Univ. Carlos III de Madrid, Spain, e-mail: fjp@estecon.uc3m.es. Research supported by Spanish MEC grants BEC2000-0167 and PB98-0728, ES
Abstract: The efficient combination of directions is a significant problem in line search methods that either use negative curvature, or wish to include additional information such as the gradient or different approximations to the Newton direction. In this paper we describe a new procedure to combine several of these directions within an interior-point primal-dual algorithm. Basically, we combine in an efficient manner a modified Newton direction with the gradient of a merit function and a direction of negative curvature, if it exists. We also show that the procedure is well-defined, and it has reasonable theoretical properties regarding the rate of convergence of the method. We also present numerical results from an implementation of the proposed algorithm on a set of small test problems from the CUTE collection. Received: November 2000 / Accepted: October 2002 Published online: February 14, 2003 Key Words. negative curvature – primal-dual methods – interior-point methods – nonconvex optimization – line searches Mathematics Subject Classification (1991): 49M37, 65K05, 90C30
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