Entropy-like proximal algorithms based on a second-order homogeneous distance function for quasi-convex programming

DOI10.1007/s10898-007-9156-yzbMath1190.90144OpenAlexW2130533809MaRDI QIDQ925232

Shaohua Pan, Jein-Shan Chen

Publication date: 3 June 2008

Published in: Journal of Global Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10898-007-9156-y

zbMATH Keywords

Entropy-like distanceProximal-like methodQuasi-convex programming

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26)

Related Items (12)

Interior quasi-subgradient method with non-Euclidean distances for constrained quasi-convex optimization problems in Hilbert spaces ⋮ An inexact proximal method for quasiconvex minimization ⋮ Full convergence of the proximal point method for quasiconvex functions on Hadamard manifolds ⋮ A generalized proximal linearized algorithm for DC functions with application to the optimal size of the firm problem ⋮ An inexact scalarization proximal point method for multiobjective quasiconvex minimization ⋮ An extension of proximal methods for quasiconvex minimization on the nonnegative orthant ⋮ Bregman proximal point type algorithms for quasiconvex minimization ⋮ Proximal point method for minimizing quasiconvex locally Lipschitz functions on Hadamard manifolds ⋮ An interior proximal linearized method for DC programming based on Bregman distance or second-order homogeneous kernels ⋮ A proximal method with separable Bregman distances for quasiconvex minimization over the nonnegative orthant ⋮ An extension of the proximal point algorithm beyond convexity ⋮ On strongly quasiconvex functions: existence results and proximal point algorithms

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