首页 | 本学科首页   官方微博 | 高级检索  
     


Flow Search Approach and New Bounds for the m-Step Linear Conjugate Gradient Algorithm
Authors:Huang  H. X.  Liang  Z. A.  Pardalos  P. M.
Affiliation:(1) Department of Mathematical Sciences, Tsinghua University, Beijing, PRC;(2) Department of Applied Mathematics, Shanghai University of Finance and Economics, Shanghai, PRC;(3) Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida
Abstract:A flow search approach is presented in this paper. In the approach, each iterative process involves a subproblem, whose variables are the stepsize parameters. Every feasible solution of the subproblem corresponds to some serial search stages, the stepsize parameters in different search stages may interact mutually, and their optimal values are determined by evaluating the total effect of the interaction. The main idea of the flow search approach is illustrated via the minimization of a convex quadratic function. Based on the flow search approach, some properties of the m-step linear conjugate gradient algorithm are analyzed and new bounds on its convergence rate are also presented. Theoretical and numerical results indicate that the new bounds are better than the well-known ones.
Keywords:Flow search approach  conjugate gradient algorithm  m-step linear conjugate gradient algorithm  convergence rate
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