@article{
 title = {A new nonlinear conjugate gradient coefficient for unconstrained optimization},
 type = {article},
 year = {2015},
 identifiers = {[object Object]},
 keywords = {Mohamed Hamoda,Mohd Rivaie,Mustafa Mamat,Zabidi},
 pages = {1813-1822},
 volume = {9},
 websites = {http://www.m-hikari.com/ams/ams-2015/ams-37-40-2015/411994.html},
 id = {e45aad32-40fa-32c0-bacf-69aca15f1437},
 created = {2015-10-25T02:24:45.000Z},
 accessed = {2015-10-25},
 file_attached = {true},
 profile_id = {f5deb0ab-f689-307d-a98f-e8991e8cc6e8},
 last_modified = {2015-10-25T04:06:37.000Z},
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 starred = {false},
 authored = {true},
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 abstract = {In this paper, we suggest a new nonlinear conjugate gradient method for solving large scale unconstrained optimization problems. We prove that the new conjugate gradient coefficient βk with exact line search is globally convergent. Preliminary numerical results with a set of 116 unconstrained optimization problems show that βk is very promising and efficient when compared to the other conjugate gradient coefficients Fletcher - Reeves (FR) and Polak -Ribiere – Polyak (PRP) .},
 bibtype = {article},
 author = {Mohamed Hamoda, Mohd Rivaie, Mustafa Mamat, Zabidin Salleh},
 journal = {APPLIED MATHEMATICAL SCIENCES},
 number = {37}
}

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