A New Symmetric Rank One Algorithm for Unconstrained Optimization | Zendy

Abbas Al-Bayati | Zendy; Salah Gazi Shareef | Zendy

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A New Symmetric Rank One Algorithm for Unconstrained Optimization

Author(s) -

Abbas Al-Bayati,

Salah Gazi Shareef

Publication year - 2011

Publication title -

maǧallaẗ al-rāfidayn li-ʿulūm al-ḥāsibāt wa-al-riyāḍiyyāẗ/al-rafidain journal for computer sciences and mathematics

Language(s) - English

Resource type - Journals

eISSN - 2311-7990

pISSN - 1815-4816

DOI - 10.33899/csmj.2011.163637

Subject(s) - broyden–fletcher–goldfarb–shanno algorithm , positive definite matrix , rank (graph theory) , matrix (chemical analysis) , mathematics , algorithm , symmetric matrix , gradient descent , mathematical optimization , computer science , combinatorics , artificial intelligence , computer network , eigenvalues and eigenvectors , physics , materials science , asynchronous communication , quantum mechanics , artificial neural network , composite material

In this paper, a new symmetric rank one for unconstrained optimization problems is presented. This new algorithm is used to solve symmetric and positive definite matrix. The new method is tested numerically by (7) nonlinear test functions and method is compared with the standard BFGS algorithm. The new matrix used is symmetric and positive definite and it generates descent directions and satisfied QN-like condition.

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