Mustafa, Mamat and Aliyu Usman, Moyi and Wah June, Leong (2014) Scaling strategies for symmetric rank-one method in solving unconstrained optimization problems. Applied Mathematical Sciences, 8 (25). pp. 1247-1260. ISSN 13147552 [P]
Image
FH02-FIK-14-00733.jpg Restricted to Registered users only Download (205kB) |
Abstract
Symmetric rank-one update (SR1) is known to have good numerical performance among the quasi-Newton methods for solving unconstrained optimization problems as evident from the recent study of Farzin et al. (2011), However, it is well known that the SR1 update may not preserve positive definiteness even when updated from a positive definite approximation and can be undefined with zero denominator. In this paper, we propose some scaling strategies to overcome these well known shortcomings of the SR1 update. Numerical experiment showed that the proposed strategies are very competitive, encouraging and have exhibited a clear improvement in the numerical performance over SR1 algorithms with some existing strategies in avoiding zero denominator and preserving positive-definiteness.
Item Type: | Article |
---|---|
Uncontrolled Keywords: | Unconstrained optimization, symmetric rank-one update, Nonpositive-definiteness, Scaling |
Subjects: | Q Science > QA Mathematics |
Divisions: | Faculty of Informatics & Computing |
Depositing User: | Syahmi Manaf |
Date Deposited: | 13 Sep 2022 05:32 |
Last Modified: | 13 Sep 2022 05:32 |
URI: | http://eprints.unisza.edu.my/id/eprint/5079 |
Actions (login required)
View Item |