A unified nonlinear augmented Lagrangian approach for nonconvex vector optimization

In this paper, we propose a unifiednonlinear augmented Lagrangian dual approach for a nonconvex vectoroptimization problem by applying a class of vector-valued nonlinearaugmented Lagrangian penalty functions. We establish weak and strongduality results, necessary and sufficient conditions for uniformlyexact penalization and exact penalization in the framework ofnonlinear augmented Lagrangian.