Positive definiteness of high-order subdifferential and high-order optimality conditions in vector optimization problems
From MaRDI portal
Publication:1949495
DOI10.1155/2013/678154zbMath1270.90065OpenAlexW2060258846WikidataQ58916574 ScholiaQ58916574MaRDI QIDQ1949495
Publication date: 8 May 2013
Published in: Abstract and Applied Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1155/2013/678154
Multi-objective and goal programming (90C29) Optimality conditions and duality in mathematical programming (90C46)
Cites Work
- Unnamed Item
- Conic positive definiteness and sharp minima of fractional orders in vector optimization problems
- Generalized Hessian matrix and second-order optimality conditions for problems with \(C^{1,1}\) data
- Sharp minima for multiobjective optimization in Banach spaces
- Nonsmooth analysis
- Weak Pareto-optimal necessary conditions in a nondifferentiable multiobjective program on a Banach space
- Pareto optimization in infinite dimensional spaces: The importance of nuclear cones
- Multiobjective optimization problem with variational inequality constraints
- Variational methods in partially ordered spaces
- Vector optimization. Set-valued and variational analysis.
- The Fermat rule for multifunctions on Banach spaces
- Weak sharp minima revisited. II: Application to linear regularity and error bounds
- Characterization of nonsmooth functions through their generalized gradients
- Weak Sharp Minima for Semi-infinite Optimization Problems with Applications
- Optimization and nonsmooth analysis
- Existence and characterization of efficient decisions with respect to cones
- Degrees of Efficiency and Degrees of Minimality
- Taylor’s Formula for $C^{k,1} $ Functions
- Weak Sharp Minima: Characterizations and Sufficient Conditions
This page was built for publication: Positive definiteness of high-order subdifferential and high-order optimality conditions in vector optimization problems
