Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
473550 | Computers & Mathematics with Applications | 2008 | 14 Pages |
Abstract
This paper proposes a new robust and quickly convergent pattern search method based on an implementation of OCSSR1 (Optimal Conditioning Based Self-Scaling Symmetric Rank-One) algorithm [M.R. Osborne, L.P. Sun, A new approach to symmetric rank-one updating, IMA Journal of Numerical Analysis 19 (1999) 497–507] for unconstrained optimization. This method utilizes the factorization of approximating Hessian matrices to provide a series of convergent positive bases needed in pattern search process. Numerical experiments on some famous optimization test problems show that the new method performs well and is competitive in comparison with some other derivative-free methods.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Ting Wu, Linping Sun,