Arah carian baru jenis kaedah kecerunan konjugat bagi kaedah kuasi-newton untuk pengoptimuman tak berkekangan

The quasi-Newton method is used extensively in solving unconstrained optimization problems. The most popular methods in quasi-Newton are Broyden-Fletcher-Goldfarb-Shanno (BFGS) and Broyden Family method. The convergence of quasi-Newton method depends on three factors which are search direction,...

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Bibliographic Details
Main Author: Mohd Asrul Hery Ibrahim (Author)
Corporate Author: Universiti Sultan Zainal Abidin . Faculty of Informatics and Computing
Format: Thesis Book
Language:Malay
Subjects:

MARC

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100 0 |a Mohd Asrul Hery Ibrahim ,   |e author 
245 1 0 |a Arah carian baru jenis kaedah kecerunan konjugat bagi kaedah kuasi-newton untuk pengoptimuman tak berkekangan   |c Mohd Asrul Hery bin Ibrahim 
264 0 |c 2015 
300 |a xvi, 193 leaves :   |b ill. ;   |c 30 cm. 
336 |a text  |2 rdacontent 
337 |a unmediated  |2 rdamedia 
338 |a volume  |2 rdacarrier 
502 |a Thesis (Degree of Doctor of Philosophy) - Universiti Sultan Zainal Abidin, 2015 
504 |a Includes bibliographical references (leaves 106-111) 
505 0 |a 1. Pengenalan -- 2. Asas pengoptimuman -- 3. Kaedah-kaedah dalam pengoptimuman tak berkekangan -- 4. Kacukan arah carian QN-SD dengan pemalar tetap -- 5. Arah carian baru bagi kaedah QN menggunakan pendekatan CG -- 6. Kaedah kacukan QN-CG -- 7. Kesimpulan dan cadangan 
520 |a The quasi-Newton method is used extensively in solving unconstrained optimization problems. The most popular methods in quasi-Newton are Broyden-Fletcher-Goldfarb-Shanno (BFGS) and Broyden Family method. The convergence of quasi-Newton method depends on three factors which are search direction, step size and approximation of Hessian. In this research, three new search directions of quasi-Newton method have been introduced. The suggested search directions are hybrid quasi-Newton method with steepest descent method, hybrid quasi-Newton method with conjugate gradient method and also quasi-Newton method by employing the conjugate gradient coefficient. The three search directions are named as quasi-Newtonsteepest descent method (ON-SD), quasi-Newton-conjugate gradient method (ON-CG) and M-quasi-Newton method (M-ON) respectively. It is proven theoretically that all these new search direction formulas fulfilled the sufficient descent condition and global convergence properties. The search direction is tested based on twenty four standard problems of unconstrained optimization. The selected standard problems cover from the small scale to large scale problems. Each of them is tested using three different initial points with a total of 180 problems using Matlab 2012. The three initial points used ranges from a point closest to the optimal point to the furthest. The effectiveness of these proposed search direction is compared with the original quasi-Newton's search direction. Numerical results obtained from the Matlab programming was based on the number of iteration, number of function evaluations and CPU-time. These results were then analyzed using performance profile by Dolan and More. The result showed that all the proposed search direction for quasi-Newton method indeed is effective compared to the original method. These results also show that these methods possess global convergence properties. It is also shown that the numerical results concur with the theoretical proof. 
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 Boundary value problems 
650 0 |a Difference equations 
650 0 |a Newton-Raphson method 
655 0 |a Dissertations, Academic 
710 2 |a Universiti Sultan Zainal Abidin .   |b Faculty of Informatics and Computing 
999 |a 1000000343   |b Thesis   |c Reference   |e Tembila Campus