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A unified nonlinear augmented Lagrangian approach for nonconvex vector optimization

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  • In this paper, we propose a unified nonlinear augmented Lagrangian dual approach for a nonconvex vector optimization problem by applying a class of vector-valued nonlinear augmented Lagrangian penalty functions. We establish weak and strong duality results, necessary and sufficient conditions for uniformly exact penalization and exact penalization in the framework of nonlinear augmented Lagrangian.
    Mathematics Subject Classification: Primary: 90C29; Secondary: 90C46.


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