Solving unconstrained optimization problems using modified conjugate gradient parameter with sufficient descent condition

Conjugate gradient (CG) methods are used for solving unconstrained optimization problem. Recently, various studies and modifications have been carrying out to improve these methods. This study proposed a new modification of Hestenes and Steifel (HS) parameter for solving unconstrained optimization p...

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Bibliographic Details
Main Author: Kamilu Uba Kamfa (Author)
Corporate Author: Universiti Sultan Zainal Abidin . Faculty of informatics and Computing
Format: Thesis Book
Language:English
Subjects:

MARC

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090 0 0 |a QA218   |b .K36 2015 
100 1 |a Kamilu Uba Kamfa ,   |e author 
245 1 0 |a Solving unconstrained optimization problems using modified conjugate gradient parameter with sufficient descent condition   |c Kamilu Uba Kamfa 
264 0 |c 2015 
300 |a xiii, 131 leaves ;   |c 30 cm. 
336 |a text  |2 rdacontent 
337 |a unmediated  |2 rdamedia 
338 |a volume  |2 rdacarrier 
502 |a Thesis (Degree of Master) - Universiti Sultan Zainal Abidin, 2015 
504 |a Includes bibliographical references (leaves 86-88) 
505 0 |a 1. Introduction -- 2. Mathematical review in optimization -- 3. Unconstrained optimization methods -- 4. A conjugate gradient methods -- 5. Numerical results and discussion -- 6. Conclusion and recommendations 
520 |a Conjugate gradient (CG) methods are used for solving unconstrained optimization problem. Recently, various studies and modifications have been carrying out to improve these methods. This study proposed a new modification of Hestenes and Steifel (HS) parameter for solving unconstrained optimization problem using exact line searches. The modification is motivated by Hestenes and Steife1 formula, where the denominator is change while holding the numerator. This modified parameter fJk has been tested using seventeen standard optimization test problems utilizing MATLAB 7.10.0 subroutine programming and the outcome is recorded. The performance of this newly parameter based on the and the number of iteration and CPU time is compared with the performance of other CG parameters which include Fletcher and Reeves (FR , Polak, Ribiere and Polyak (pRP), Abdelrhaman, Mustafa, Rivaie and Ismail (AMRI) method. In fact, for each test problems four different initial points is considered ranges from the one near to the solution point to one further away. The numerical results have shown that this modified parameter performs better than FR, PRP and AMRI methods, while it holds its simplicity and possesses the global convergence properties. 
610 2 0 |a Universiti Sultan Zainal Abidin   |x Dissertations 
610 2 0 |a Universiti Sultan Zainal Abidin   |x Faculty of Informatics and Computing   |v Dissertations 
650 0 |a Conjugate gradient methods 
655 0 |a Dissertations, Academic 
710 2 |a Universiti Sultan Zainal Abidin .   |b Faculty of informatics and Computing 
999 |a 1000165545   |b Thesis   |c Reference   |e Tembila Campus