Line Search Methods in Conjugate Gradient Algorithms - Babaeizadeh, Soudeh;Ahmad, Rohanin
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Nonlinear conjugate gradient methods (CG) are especially efficient methods for the solution of the large scale unconstrained optimization problems, as these methods are characterized by low memory requirement and strong local and global convergence properties. However, line search in CG methods is of critical importance. Reducing line search cost in conjugate gradient algorithm is the main objective of this monograph. Based on the type of the line searches applied in the CG method, these methods are generally divided into three approaches. The conjugate gradient methods with exact line search,…mehr

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Produktbeschreibung
Nonlinear conjugate gradient methods (CG) are especially efficient methods for the solution of the large scale unconstrained optimization problems, as these methods are characterized by low memory requirement and strong local and global convergence properties. However, line search in CG methods is of critical importance. Reducing line search cost in conjugate gradient algorithm is the main objective of this monograph. Based on the type of the line searches applied in the CG method, these methods are generally divided into three approaches. The conjugate gradient methods with exact line search, inexact line search and conjugate gradient without any line search. This study is intended to compare and analyze the efficiency and effectiveness of these optimization techniques through numerical simulations.
Autorenporträt
Soudeh Babaeizadeh received the master degree in the operational research field at UTM Malaysia. She is currently a PhD student at the same university.Rohanin Ahmad did her master degree at Indiana State University. She got her PhD from UTM Malaysia in the field of optimal control. Most of the researches that they are involved now are in this area