New Inexact Line Search Method for Unconstrained Optimization

被引:0
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作者
Z. J. Shi
J. Shen
机构
[1] Qufu Normal University,College of Operations Research and Management
[2] Academy of Mathematics and Systems Science,Institute of Computational Mathematics and Scientific/Engineering Computing
[3] Chinese Academy of Sciences,Department of Computer and Information Science
[4] University of Michigan,undefined
关键词
Unconstrained optimization; inexact line search; global convergence; convergence rate;
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摘要
We propose a new inexact line search rule and analyze the global convergence and convergence rate of related descent methods. The new line search rule is similar to the Armijo line-search rule and contains it as a special case. We can choose a larger stepsize in each line-search procedure and maintain the global convergence of related line-search methods. This idea can make us design new line-search methods in some wider sense. In some special cases, the new descent method can reduce to the Barzilai and Borewein method. Numerical results show that the new line-search methods are efficient for solving unconstrained optimization problems.
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页码:425 / 446
页数:21
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