Global convergence of a new spectral conjugate gradient by using strong wolfe line search
Unconstrained optimization problems can be solved by using few popular methods such as Conjugate Gradient (CG) method, Steepest Descent (SD) Method and Broyden-Fletcher-Goldfarb-Shanno (BFGS) method. The simplest solving method is by using SD method but nowadays CG method is used worldwide due to it...
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| المؤلفون الرئيسيون: | , , |
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| التنسيق: | مقال |
| اللغة: | English |
| منشور في: |
HIKARI Ltd.
2015
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://eprints.unisza.edu.my/6330/1/FH02-FIK-15-03433.jpg http://eprints.unisza.edu.my/6330/ |
| الوسوم: |
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| الملخص: | Unconstrained optimization problems can be solved by using few popular methods such as Conjugate Gradient (CG) method, Steepest Descent (SD) Method and Broyden-Fletcher-Goldfarb-Shanno (BFGS) method. The simplest solving method is by using SD method but nowadays CG method is used worldwide due to its convergence analysis. A few of unconstrained optimization problems with several different variables are used to prove the global convergence result of new spectral conjugate gradient to be compared with five most common k proposed by the early researches by using inexact line search. |
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