Pareto efficiency in locally convex spaces i

DOI10.1080/01630568508816205zbMath0665.49003OpenAlexW2030652436MaRDI QIDQ3816593

Nikolaos S. Papageorgiou

Publication date: 1985

Published in: Numerical Functional Analysis and Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01630568508816205

zbMATH Keywords

locally convex spacesPareto efficiencyset valued integration

Mathematics Subject Classification ID

Sensitivity, stability, parametric optimization (90C31) Programming in abstract spaces (90C48) Methods involving semicontinuity and convergence; relaxation (49J45) Existence theories for problems in abstract spaces (49J27)

Related Items (11)

Random approximations in multiobjective optimization ⋮ Remarks on convex cones ⋮ Nonsmooth analysis on partially ordered vector spaces: the subdifferential theory ⋮ On the connectedness of the set of weakly efficient points of a vector optimization problem in locally convex spaces ⋮ A new representation of efficient point sets and its applications in DEA ⋮ Connectedness of cone superefficient point sets in locally convex topological vector spaces ⋮ On stability in multiobjective programming. A stochastic approach ⋮ Approximate proper solutions in vector equilibrium problems. Limit behavior and linear scalarization results ⋮ Approximating families of cones and proper efficiency in vector optimization ⋮ Limit Behavior of Approximate Proper Solutions in Vector Optimization ⋮ Relationship between solid cones and cones with bases

Cites Work

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• Existence of efficient solutions for vector maximization problems
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• Integrals of set-valued functions
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• Measurable dependence of convex sets and functions on parameters
• Cone convexity, cone extreme points, and nondominated solutions in decision problems with multiobjectives
• Monotone Operators and the Proximal Point Algorithm
• Proper Efficient Points for Maximizations with Respect to Cones
• An existence theorem for pareto problems
• Sous-Différentiabilité de fonctions convexes à valeurs dans un espace vectoriel ordonné.
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