A quasi-Newton algorithm for nonconvex, nonsmooth optimization with global convergence guarantees

DOI10.1007/s12532-015-0086-2zbMath1333.49042OpenAlexW902317526MaRDI QIDQ903922

Xiaocun Que, Frank E. Curtis

Publication date: 15 January 2016

Published in: Mathematical Programming Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s12532-015-0086-2

zbMATH Keywords

unconstrained optimizationnonsmooth optimizationnonconvex optimizationquasi-Newton methodsline search methodsgradient sampling

Mathematics Subject Classification ID

Related Items (10)

Limited-memory BFGS with displacement aggregation ⋮ Manifold Sampling for Optimization of Nonconvex Functions That Are Piecewise Linear Compositions of Smooth Components ⋮ A hierarchy of spectral relaxations for polynomial optimization ⋮ Trust-region algorithms for training responses: machine learning methods using indefinite Hessian approximations ⋮ A New Sequential Optimality Condition for Constrained Nonsmooth Optimization ⋮ An SL/QP Algorithm for Minimizing the Spectral Abscissa of Time Delay Systems ⋮ A limited-memory quasi-Newton algorithm for bound-constrained non-smooth optimization ⋮ A fast gradient and function sampling method for finite-max functions ⋮ A geometric integration approach to nonsmooth, nonconvex optimisation ⋮ Solving an inverse heat convection problem with an implicit forward operator by using a projected quasi-Newton method

Uses Software

• L-BFGS
• UFO
• PLCP
• SQPlab
• HIFOO
• GradSamp
• HANSO
• Armadillo
• LDGB

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