On Parametric Vector Optimization via Metric Regularity of Constraint Systems

TL;DR

This paper investigates metric and graphical regularity properties of constraint systems and applies these properties to derive necessary optimality conditions in constrained vector optimization problems.

Contribution

It introduces new regularity properties and uses them to establish optimality conditions in vector optimization, advancing the theoretical framework.

Findings

Regularity properties of constraint systems are characterized.

Necessary optimality conditions are derived for constrained vector optimization.

The approach enhances understanding of constraint regularity in optimization.

Abstract

Some metric and graphical regularity properties of generalized constraint systems are investigated. Then, these properties are applied in order to penalize (in the sense of Clarke) various scalar and vector optimization problems. This method allows us to present several necessary optimality conditions in solid constrained vector optimization.