Approximate solutions of vector optimization problems via improvement sets in real linear spaces
We consider the notions of approximate efficient solution and approximate weak efficient solution of a vector optimization problem based on improvement sets in the framework of real linear spaces, i.e., without using topological tools. It is well known that the analogous concepts in topological vector spaces unify several notions of exact and approximate efficient solutions. Some characterizations of the weak notion are provided by linear scalarization in problems with abstract constraints, and by scalar Lagrange optimality conditions in cone-constrained problems. For such aim we use a new notion of generalized convexity, called generalized subconvexlike with respect to an improvement set. We illustrate our results with an example.
Palabras clave / Keywords: vector optimization approximate weak efficiency improvement set
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