Second order convexity and a modified objective function method in mathematical programming
Tadeusz Antczak (2007)
Control and Cybernetics
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Displaying similar documents to “LFS functions in multi-objective programming”
Second order convexity and a modified objective function method in mathematical programming
Two characterizations of Pareto minima in convex multicriteria optimization
Sanjo Zlobec (1984)
Aplikace matematiky
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Two conditions are given each of which is both necessary and sufficient for a point to be a global Pareto minimum. The first one is obtained by studying programs where each criterion appears as a single objective function, while the second one is given in terms of a "restricted Lagrangian". The conditions are compared with the familiar characterizations of properly efficient and weakly efficient points of Karlin and Geoffrion.
Second-order optimality conditions for nondominated solutions of multiobjective programming with data
Liping Liu, Pekka Neittaanmäki, Michal Křížek (2000)
Applications of Mathematics
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We examine new second-order necessary conditions and sufficient conditions which characterize nondominated solutions of a generalized constrained multiobjective programming problem. The vector-valued criterion function as well as constraint functions are supposed to be from the class . Second-order optimality conditions for local Pareto solutions are derived as a special case.