A simple constraint qualification in convex programming

A simple constraint qualification in convex programming

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Article ID: iaor19942383
Country: Netherlands
Volume: 61
Issue: 3
Start Page Number: 385
End Page Number: 397
Publication Date: Sep 1993
Journal: Mathematical Programming (Series A)
Authors: , ,
Keywords: programming: multiple criteria
Abstract:

The authors introduce and characterize a class of differentiable convex functions for which the Karush-Kuhn-Tucker condition is necessary for optimality. If some constraints do not belong to this class, then the characterization of optimality generally assumes to asymptotic form. The authors also show that for the functions that belong to this class in multi-objective optimization, Pareto solutions coincide with strong Pareto solutions. This extends a result, well known for the linear case.

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