A gradient sampling method based on ideal direction for solving nonsmooth optimization problems

DOI10.1007/s10957-020-01740-8zbMath1467.90042OpenAlexW3081934664MaRDI QIDQ831368

Morteza Maleknia, Mostafa Shamsi

Publication date: 11 May 2021

Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10957-020-01740-8

zbMATH Keywords

subdifferentialArmijo line searchgradient samplingsteepest descent directionnonsmooth and nonconvex optimization

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonconvex programming, global optimization (90C26)

Related Items (1)

A quasi-Newton proximal bundle method using gradient sampling technique for minimizing nonsmooth convex functions

Uses Software

• UFO
• GradSamp
• LDGB

Cites Work

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• Multicriteria Optimization
• A Robust Gradient Sampling Algorithm for Nonsmooth, Nonconvex Optimization
• New limited memory bundle method for large-scale nonsmooth optimization
• Convex Analysis
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