Characterizations of robust optimality conditions via image space analysis
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Publication:5121775
DOI10.1080/02331934.2020.1728269zbMath1477.90050OpenAlexW3007423676MaRDI QIDQ5121775
Pradeep Sharma, Xiaolong Qin, Qamrul Hasan Ansari
Publication date: 19 September 2020
Published in: Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/02331934.2020.1728269
shortest path problemimage space analysisnonlinear scalarizationuncertain optimizationrobust optimality conditions
Nonlinear programming (90C30) Optimality conditions and duality in mathematical programming (90C46) Robustness in mathematical programming (90C17)
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Cites Work
- Unnamed Item
- Minmax robustness for multi-objective optimization problems
- A general vectorial Ekeland's variational principle with a P-distance
- Concepts of efficiency for uncertain multi-objective optimization problems based on set order relations
- Nonconvex separation theorems and some applications in vector optimization
- Weak efficiency in vector optimization using a closure of algebraic type under cone-convexlikeness.
- Image space analysis for constrained inverse vector variational inequalities via multiobjective optimization
- Characterizations for optimality conditions of general robust optimization problems
- Nonlinear separation approach to inverse variational inequalities in real linear spaces
- Characterizations of multiobjective robustness via oriented distance function and image space analysis
- On robust multiobjective optimization
- Constrained optimization and image space analysis. Vol. 1: Separation of sets and optimality conditions
- Statistical decision functions which minimize the maximum risk
- Nonlinear separation approach to inverse variational inequalities
- Vector Optimization
- Introduction to Stochastic Programming
- Characterizations of set relations with respect to variable domination structures via oriented distance function
- Nonconvex Separation Functional in Linear Spaces with Applications to Vector Equilibria
- Technical Note—Convex Programming with Set-Inclusive Constraints and Applications to Inexact Linear Programming
- Robustness for uncertain multi-objective optimization: a survey and analysis of different concepts