The projected gradient direction in vector optimization: continuity and dual characterization
; Prudente, L. F. ; Schuverdt, María Laura 
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02/2026
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Springer
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Computational And Applied Mathematics
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2238-3603
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Inglés
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This technical note proves that, for a smooth vector optimization problem on a closed convexfeasible set ordered by a pointed cone, the projected gradient direction depends continuously on the decision variable. Our argument is based on a simple and direct proof viaa fixed-domain reformulation of the subproblem. We then give a necessary and sufficientdual characterization of this direction and show that its associated set-valued dual variablemapping is outer semicontinuous.
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