A Conjugate Gradient Algorithm under Yuan-Wei-Lu Line Search Technique for Large-Scale Minimization Optimization Models
2018 ◽
Vol 2018
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pp. 1-11
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Keyword(s):
This paper gives a modified Hestenes and Stiefel (HS) conjugate gradient algorithm under the Yuan-Wei-Lu inexact line search technique for large-scale unconstrained optimization problems, where the proposed algorithm has the following properties: (1) the new search direction possesses not only a sufficient descent property but also a trust region feature; (2) the presented algorithm has global convergence for nonconvex functions; (3) the numerical experiment showed that the new algorithm is more effective than similar algorithms.
2017 ◽
Vol 95
(2)
◽
pp. 382-395
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2020 ◽
Vol 20
(2)
◽
pp. 939
2019 ◽
Vol 2019
(1)
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2018 ◽
Vol 2018
(1)
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2015 ◽
Vol 92
◽
pp. 70-81
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2021 ◽
pp. 2150053
2019 ◽
Vol 362
◽
pp. 262-275
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2005 ◽
Vol 125
(3)
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pp. 523-541
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2020 ◽
Vol 18
(5)
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pp. 1179-1190