Duality in vector optimization
Copyright policy )Duality in vector optimization
In this paper the problem dual to a convex vector optimization problem is defined. Under suitable assumptions, a weak, strong and strict converse duality theorem are proved. In the case of linear mappings the formulation of the dual is refined such that well-known dual problems of Gale, Kuhn and Tucker [8] and Isermann [12] are generalized by this approach.
Programming in abstract spaces, strict converse duality theorem, convex vector optimization, strong converse duality, dual problem, Sensitivity, stability, parametric optimization, weak converse duality, Duality theory (optimization)
Programming in abstract spaces, strict converse duality theorem, convex vector optimization, strong converse duality, dual problem, Sensitivity, stability, parametric optimization, weak converse duality, Duality theory (optimization)
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