Strong duality in robust semi-definite linear programming under data uncertainty

DOI10.1080/02331934.2012.690760zbMath1291.90164OpenAlexW2034371146WikidataQ59241494 ScholiaQ59241494MaRDI QIDQ5169452

Guoyin Li, Vaithilingam Jeyakumar

Publication date: 10 July 2014

Published in: Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331934.2012.690760

zbMATH Keywords

robust optimizationstrong dualitylinear matrix inequality problemssemi-definite programming under uncertainty

Mathematics Subject Classification ID

Semidefinite programming (90C22) Convex programming (90C25) Optimality conditions and duality in mathematical programming (90C46)

Related Items (10)

On approximate solutions for robust convex semidefinite optimization problems ⋮ A Framework for Solving Chance-Constrained Linear Matrix Inequality Programs ⋮ Approximate optimality and approximate duality for quasi approximate solutions in robust convex semidefinite programs ⋮ Duality theorems for convex and quasiconvex set functions ⋮ On optimality conditions and duality theorems for robust semi-infinite multiobjective optimization problems ⋮ On robust duality for fractional programming with uncertainty data ⋮ A discussion on the conservatism of robust linear optimization problems ⋮ On approximate solutions for robust semi-infinite multi-objective convex symmetric cone optimization ⋮ Strong duality for robust minimax fractional programming problems ⋮ Surrogate duality for robust optimization

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