Separation theorems for nonconvex sets and application in optimization

DOI10.1016/j.orl.2019.09.011zbMath1476.90260OpenAlexW2978839893MaRDI QIDQ2294382

Refail Kasimbeyli, Masoud Karimi

Publication date: 10 February 2020

Published in: Operations Research Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.orl.2019.09.011

zbMATH Keywords

nonconvex optimizationaugmented dual conesnonlinear separation theorem

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26)

Related Items (5)

A polyhedral conic functions based classification method for noisy data ⋮ Generalized derivatives and optimality conditions in nonconvex optimization ⋮ Nonlinear Cone Separation Theorems in Real Topological Linear Spaces ⋮ On weak conjugacy, augmented Lagrangians and duality in nonconvex optimization ⋮ Duality in nonconvex vector optimization

Cites Work

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• Nonconvex separation theorems and some applications in vector optimization
• Optimality conditions in nonconvex optimization via weak subdifferentials
• Hartley properly and super nondominated solutions in vector optimization with a variable ordering structure
• Hahn-Banach extension theorems for multifunctions revisited
• A cone separation theorem
• Maximum principle in the problem of time optimal response with nonsmooth constraints
• Generalized differential calculus for nonsmooth and set-valued mappings
• A coradiant based scalarization to characterize approximate solutions of vector optimization problems with variable ordering structures
• Combined forecasts in portfolio optimization: a generalized approach
• A generalization of Hahn--Banach extension theorem
• On augmented Lagrangians for optimization problems with a single constraint
• Augmented Lagrangian duality and nondifferentiable optimization methods in nonconvex programming
• Existence and characterization theorems in nonconvex vector optimization
• A conic scalarization method in multi-objective optimization
• A generalization of a theorem of Arrow, Barankin and Blackwell to a nonconvex case
• On Weak Subdifferentials, Directional Derivatives, and Radial Epiderivatives for Nonconvex Functions
• A Nonlinear Cone Separation Theorem and Scalarization in Nonconvex Vector Optimization
• Variational Analysis
• Strictly Increasing Positively Homogeneous Functions with Application to Exact Penalization
• The modified subgradient algorithm based on feasible values
• Set-valued Optimization

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