Wujie Hu1, Gonglin Yuan1, *, Hongtruong Pham2
CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 787-800, 2020, DOI:10.32604/cmc.2020.02993
Abstract It is well known that Newton and quasi-Newton algorithms are effective to small
and medium scale smooth problems because they take full use of corresponding gradient
function’s information but fail to solve nonsmooth problems. The perfect algorithm stems
from concept of ‘bundle’ successfully addresses both smooth and nonsmooth complex
problems, but it is regrettable that it is merely effective to small and medium optimization
models since it needs to store and update relevant information of parameter’s bundle. The
conjugate gradient algorithm is effective both large-scale smooth and nonsmooth
optimization model since its simplicity that utilizes More >
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