A subgradient method with non-monotone line search

被引：0
作者：
O. P. Ferreira
G. N. Grapiglia
E. M. Santos
J. C. O. Souza
机构：
[1] Universidade Federal de Goiás,Instituto de Matemática e Estatística
[2] Université Catholique de Louvain,ICTEAM/INMA
[3] Instituto Federal de Educação,AMSE, CNRS
[4] Ciência e Tecnologia do Maranhão,Department of Mathematics
[5] Aix-Marseille University,undefined
[6] Federal University of Piauí,undefined
来源：
Computational Optimization and Applications | 2023年 / 84卷
关键词：
Subgradient method; Non-monotone line search; Convex function;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper we present a subgradient method with non-monotone line search for the minimization of convex functions with simple convex constraints. Different from the standard subgradient method with prefixed step sizes, the new method selects the step sizes in an adaptive way. Under mild conditions asymptotic convergence results and iteration-complexity bounds are obtained. Preliminary numerical results illustrate the relative efficiency of the proposed method.
引用
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页码：397 / 420
页数：23
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