Global Convergence of an Extended Descent Algorithm without Line Search for Unconstrained Optimization

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DOI: 10.4236/jamp.2018.61013    857 Downloads   1,843 Views  Citations

ABSTRACT

In this paper, we extend a descent algorithm without line search for solving unconstrained optimization problems. Under mild conditions, its global convergence is established. Further, we generalize the search direction to more general form, and also obtain the global convergence of corresponding algorithm. The numerical results illustrate that the new algorithm is effective.

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Chen, C. , Luo, L. , Han, C. and Chen, Y. (2018) Global Convergence of an Extended Descent Algorithm without Line Search for Unconstrained Optimization. Journal of Applied Mathematics and Physics, 6, 130-137. doi: 10.4236/jamp.2018.61013.

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