Local saddle point and a class of convexification methods for nonconvex optimization problems

DOI10.1007/s10898-006-9090-4zbMath1175.90317OpenAlexW2014939542MaRDI QIDQ2460140

Panos M. Pardalos, Tao Li, Zhi-An Liang, Yan-Jun Wang

Publication date: 14 November 2007

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

Full work available at URL: https://doi.org/10.1007/s10898-006-9090-4

zbMATH Keywords

nonconvex optimizationconvexificationlocal convexitylocal saddle point

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26) Nonlinear programming (90C30)

Related Items (10)

An exact minimax penalty function method and saddle point criteria for nonsmooth convex vector optimization problems ⋮ A review of recent advances in global optimization ⋮ Global saddle points of nonlinear augmented Lagrangian functions ⋮ A survey of hidden convex optimization ⋮ On equivalence between a variational problem and its modified variational problem with the η‐objective function under invexity ⋮ Saddle points criteria in nondifferentiable multiobjective programming with \(V\)-invex functions via an \(\eta \)-approximation method ⋮ Duality for a fractional variational formulation using $\eta$-approximated method ⋮ Saddle points of general augmented Lagrangians for constrained nonconvex optimization ⋮ Second order modified objective function method for twice differentiable vector optimization problems over cone constraints ⋮ Strong duality in optimization: shifted power reformulation

Cites Work

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• Local saddle points and convexification for nonconvex optimization problems
• Zero duality gap for a class of nonconvex optimization problems
• Local convexification of the Lagrangian function in nonconvex optimization
• A duality theorem for non-linear programming

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