Pareto Optimizing and Kuhn–Tucker Stationary Sequences

Abstract

We study the relation between weakly Pareto minimizing and Kuhn–Tucker stationary nonfeasible sequences for vector optimization under constraints, where the weakly Pareto (efficient) set may be empty. The work is placed in a context of Banach spaces and the constraints are described by a functional taking values in a cone. We characterize the asymptotic feasibility in terms of the constraint map and the asymptotic efficiency via a Kuhn–Tucker system completely approximate, distinguishing the classical bounded case from the nontrivial unbounded one. The latter requires Auslender–Crouzeix type conditions and Ekeland's variational principle for constrained vector problems.