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A conjugate gradient method with global convergence for large-scale unconstrained optimization problems
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نویسنده
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yao s. ,lu x. ,wei z.
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منبع
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journal of applied mathematics - 2013 - دوره : 2013 - شماره : 0
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چکیده
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The conjugate gradient (cg) method has played a special role in solving large-scale nonlinear optimization problems due to the simplicity of their very low memory requirements. this paper proposes a conjugate gradient method which is similar to dai-liao conjugate gradient method (dai and liao,2001) but has stronger convergence properties. the given method possesses the sufficient descent condition,and is globally convergent under strong wolfe-powell (swp) line search for general function. our numerical results show that the proposed method is very efficient for the test problems. © 2013 shengwei yao et al.
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آدرس
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school of science,east china university of science and technology,shanghai 200237,china,school of information and statistics,guangxi university of finance and economics, China, school of science,east china university of science and technology, China, college of mathematics and information science,guangxi university, China
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Authors
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