Guaranteeing highly robust weakly efficient solutions for uncertain multi-objective convex programs

DOI10.1016/j.ejor.2018.03.018zbMath1403.90606OpenAlexW2793406148MaRDI QIDQ1754722

José Vicente-Pérez, Guoyin Li, Miguel Angel Goberna, Vaithilingam Jeyakumar

Publication date: 31 May 2018

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10045/75950

zbMATH Keywords

multi-objective optimizationconvex optimizationrobust optimizationrobustness and sensitivity analysisrobust efficient solutions

Mathematics Subject Classification ID

Convex programming (90C25) Minimax problems in mathematical programming (90C47) Multi-objective and goal programming (90C29)

Related Items (11)

Miguel A. Goberna: ``The challenge was to bring Spanish research in mathematics to normality ⋮ On robust Karush-Kuhn-Tucker multipliers rules for semi-infinite multiobjective optimization with data uncertainty ⋮ Robust Optimality and Duality in Multiobjective Optimization Problems under Data Uncertainty ⋮ A radius of robust feasibility for uncertain farthest Voronoi cells ⋮ Unnamed Item ⋮ Recent contributions to linear semi-infinite optimization: an update ⋮ The radius of robust feasibility of uncertain mathematical programs: a survey and recent developments ⋮ Unnamed Item ⋮ The price of multiobjective robustness: analyzing solution sets to uncertain multiobjective problems ⋮ Decision making in multiobjective optimization problems under uncertainty: balancing between robustness and quality ⋮ Pareto solutions in multicriteria optimization under uncertainty

Uses Software

• BENSOLVE

Cites Work

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