Minimax programming as a tool for studying robust multi-objective optimization problems
From MaRDI portal
Publication:2108806
DOI10.1007/s10479-021-04179-wzbMath1502.90125OpenAlexW3182145356MaRDI QIDQ2108806
Zhe Hong, Do Sang Kim, Kwan Deok Bae
Publication date: 20 December 2022
Published in: Annals of Operations Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10479-021-04179-w
multi-objective optimizationgeneralized convexitydualityminimax programmingKKT optimality conditions
Related Items (4)
Optimality conditions for nondifferentiable minimax programs and vector optimization problems ⋮ Approximate optimality conditions and approximate duality theorems for nonlinear semi-infinite programming problems with uncertainty data ⋮ On approximate optimality conditions for robust multi-objective convex optimization problems ⋮ On Minimax Fractional Semi-Infinite Programming Problems with Applications
Cites Work
- Unnamed Item
- Minmax robustness for multi-objective optimization problems
- \(\varepsilon \)-mixed type duality for nonconvex multiobjective programs with an infinite number of constraints
- Nondifferentiable minimax fractional programming in complex spaces with parametric duality
- Optimality conditions and duality in nonsmooth multiobjective optimization problems
- A class of nonsmooth fractional multiobjective optimization problems
- Finding efficient solutions in robust multiple objective optimization with SOS-convex polynomial data
- Selected topics in robust convex optimization
- Duality in robust optimization: Primal worst equals dual best
- Nondifferentiable mathematical programming and convex-concave functions
- Convex programming with set-inclusive contraints and its applications to generalized linear and fractional programming
- Duality for a class of minmax and inexact programming problem
- Robust discrete optimization and its applications
- Normal regularity for the feasible set of semi-infinite multiobjective optimization problems with applications
- Optimality conditions in convex optimization with locally Lipschitz constraints
- On the existence of Pareto solutions for polynomial vector optimization problems
- Nondifferentiable minimax programming problems with applications
- Optimality conditions and duality for robust nonsmooth multiobjective optimization problems with constraints
- Deriving robust counterparts of nonlinear uncertain inequalities
- Robust Convex Optimization
- Optimization and nonsmooth analysis
- Technical Note—Exact Solutions of Inexact Linear Programs
- Robust Solutions to Uncertain Semidefinite Programs
- Robust Truss Topology Design via Semidefinite Programming
- Robust Solutions to Least-Squares Problems with Uncertain Data
- Variational Analysis and Applications
- Multicriteria Optimization
- The Lagrange Multiplier Theorem for Max-Min with Several Constraints
- Technical Note—Convex Programming with Set-Inclusive Constraints and Applications to Inexact Linear Programming
- Optimality and duality for robust multiobjective optimization problems
This page was built for publication: Minimax programming as a tool for studying robust multi-objective optimization problems