Proximal bundle algorithms for nonlinearly constrained convex minimax fractional programs

DOI10.1007/s10957-018-1342-1zbMath1409.90197OpenAlexW2835899109WikidataQ129528421 ScholiaQ129528421MaRDI QIDQ1730809

Ahmed Roubi, Smail Addoune, Karima Boufi

Publication date: 6 March 2019

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

Full work available at URL: https://doi.org/10.1007/s10957-018-1342-1

zbMATH Keywords

method of centersquadratic programmingbundle methodsproximal point algorithmgeneralized fractional programs

Mathematics Subject Classification ID

Convex programming (90C25) Fractional programming (90C32) Numerical methods based on nonlinear programming (49M37) Optimality conditions for minimax problems (49K35)

Related Items (7)

A DC approach for minimax fractional optimization programs with ratios of convex functions ⋮ Optimality conditions and a method of centers for minimax fractional programs with difference of convex functions ⋮ An entropic regularized method of centers for continuous minimax problem with semi infinite constraints ⋮ Proximal bundle methods based on approximate subgradients for solving Lagrangian duals of minimax fractional programs ⋮ Augmented Lagrangian dual for nonconvex minimax fractional programs and proximal bundle algorithms for its resolution ⋮ Optimality conditions and DC-Dinkelbach-type algorithm for generalized fractional programs with ratios of difference of convex functions ⋮ Duality Results and Dual Bundle Methods Based on the Dual Method of Centers for Minimax Fractional Programs

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