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A globally convergent gradient-like method based on the Armijo line search | ||
| Journal of Mathematical Modeling | ||
| دوره 9، شماره 4، اسفند 2021، صفحه 665-676 اصل مقاله (321.65 K) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22124/jmm.2021.18854.1612 | ||
| نویسندگان | ||
| Ahmad Kamandi* 1؛ Keyvan Amini2 | ||
| 1Department of Mathematics, University of Science and Technology of Mazandaran, Behshahr, Iran | ||
| 2Department of Mathematics, Razi university, Kermanshah, Iran | ||
| چکیده | ||
| In this paper, a new conjugate gradient-like algorithm is proposed to solve unconstrained optimization problems. The step directions generated by the new algorithm satisfy sufficient descent condition independent of the line search. The global convergence of the new algorithm, with the Armijo backtracking line search, is proved. Numerical experiments indicate the efficiency and robustness of the new algorithm. | ||
| کلیدواژه‌ها | ||
| Unconstrained optimization؛ conjugate gradient algorithm؛ global convergence؛ Armijo condition | ||
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