On Second-Order Optimality Conditions for Vector Optimization |
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Authors: | María C Maciel Sandra A Santos Graciela N Sottosanto |
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Institution: | 1.Department of Mathematics,Southern National University,Bahía Blanca,Argentina;2.Department of Applied Mathematics,State University of Campinas,Campinas,Brazil;3.Department of Mathematics,Comahue National University,Neuquén,Argentina |
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Abstract: | In this article, two second-order constraint qualifications for the vector optimization problem are introduced, that come
from first-order constraint qualifications, originally devised for the scalar case. The first is based on the classical feasible
arc constraint qualification, proposed by Kuhn and Tucker (Proceedings of the Second Berkeley Symposium on Mathematical Statistics
and Probability, vol. 1, pp. 481–492, University of California Press, California, 1951) together with a slight modification of McCormick’s second-order constraint qualification. The second—the constant rank constraint
qualification—was introduced by Janin (Math. Program. Stud. 21:110–126, 1984). They are used to establish two second-order necessary conditions for the vector optimization problem, with general nonlinear
constraints, without any convexity assumption. |
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Keywords: | |
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