A descent subgradient method using Mifflin's line search for nonsmooth nonconvex optimization

IF 1.6 3区数学 Q2 MATHEMATICS, APPLIED

Optimization Pub Date : 2024-03-01 DOI:10.1080/02331934.2024.2322152

Morteza Maleknia, Majid Soleimani-damaneh

引用次数: 0

Abstract

We propose a descent subgradient algorithm for minimizing a function f:Rn→R, assumed to be locally Lipschitz, but not necessarily smooth or convex. To find an effective descent direction, the Golds...

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利用米夫林线搜索进行非平滑非凸优化的下降子梯度法

我们提出了一种子梯度下降算法，用于最小化函数 f:Rn→R，该函数假定为局部 Lipschitz，但不一定光滑或凸。为了找到有效的下降方向，Golds...

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来源期刊

Optimization 数学-应用数学

CiteScore

4.50

自引率

9.10%

发文量

146

审稿时长

4.5 months

期刊介绍： Optimization publishes refereed, theoretical and applied papers on the latest developments in fields such as linear, nonlinear, stochastic, parametric, discrete and dynamic programming, control theory and game theory. A special section is devoted to review papers on theory and methods in interesting areas of mathematical programming and optimization techniques. The journal also publishes conference proceedings, book reviews and announcements. All published research articles in this journal have undergone rigorous peer review, based on initial editor screening and anonymous refereeing by independent expert referees.