A Line Search Algorithm for Unconstrained Optimization

Abstract

It is well known that the line search methods play a very important role for optimization problems. In this paper a new line search method is proposed for solving unconstrained optimization. Under weak conditions, this method possesses global convergence and R-linear convergence for nonconvex function and convex function, respectively. Moreover, the given search direction has sufficiently descent property and belongs to a trust region without carrying out any line search rule. Numerical results show that the new method is effective.

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G. Yuan, S. Lu and Z. Wei, "A Line Search Algorithm for Unconstrained Optimization," Journal of Software Engineering and Applications, Vol. 3 No. 5, 2010, pp. 503-509. doi: 10.4236/jsea.2010.35057.

Conflicts of Interest

The authors declare no conflicts of interest.

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