A compact limited memory method for large scale unconstrained optimization [An article from: European Journal of Operational Research]

This digital document is a journal article from European Journal of Operational Research, published by Elsevier in 2007. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
A compact limited memory method for solving large scale unconstrained optimization problems is proposed. The compact representation of the quasi-Newton updating matrix is derived to the use in the form of limited memory update in which the vector y"k is replaced by a modified vector y@?"k so that more available information about the function can be employed to increase the accuracy of Hessian approximations. The global convergence of the proposed method is proved. Numerical tests on commonly used large scale test problems indicate that the proposed compact limited memory method is competitive and efficient.