%0 Journal Article
%T Numerical Experiments with Matrices Storage Free BFGS Method for Large Scale Unconstrained Optimization
%A Malik Hj. Abu Hassan
%A Mansor Monsi
%A Leong Wah June
%J Matematika
%D 2003
%I Universiti Teknologi Malaysia
%X We study the numerical performance of a matrices storage free quasi-Newton method for large-scale optimization, which we call the F-BFGS method. We compare its performance with that of the limited memory BFGS, L-BFGS methods developed by Nocedal (1980) and the conjugate gradient methods. The F-BFGS method is very competitive due to its low storage requirement and computational labor and also able to solve large-scale problems with 106 variables successfully while other methods fail.
%K Large scale optimization
%K matrices storage free methods
%K limited memory methods
%K conjugate gradient methods.
%U http://www.fs.utm.my/matematika/images/stories/matematika/200319204.pdf