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Two characterizations of Pareto minima in convex multicriteria optimization. (English) Zbl 0549.90085

Summary: We give two conditions, 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 characterization of properly efficient and weakly efficient points of Karlin and Geoffrion.

MSC:

90C31 Sensitivity, stability, parametric optimization
90C25 Convex programming
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References:

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