Strong and weak conditions of regularity and optimality (original) (raw)

2022, Applicationes Mathematicae

Characterization of Weakly Efficient Solutions for Nonlinear Multiobjective Programming Problems. Duality

Journal of Convex Analysis

Convexity and generalized convexity play a central role in mathematical programming for duality results and in order to characterize the solutions set. In this paper, taking in mind Craven's notion of K-invexity function (when K is a cone in R-n) and Martin's notion of Karush-Kuhn-Tucker invexity (hereafter KKT-invexity), we define new notions of generalized convexity for a multiobjective problem with conic constraints. These new notions are both necessary and sufficient to ensure every Karush-Kuhn-Tucker point is a solution. The study of the solutions is also done through the solutions of an associated scalar problem. A Mond-Weir type dual problem is formulated and weak and strong duality results are provided. The notions and results that exist in the literature up to now are particular instances of the ones presented here.

Lagrange Multipliers in Multiobjective Optimization

2007

We study a multiobjective optimization problem in finite-dimensional spaces with a feasible set defined by directionally differentiable (or quasiconvex) inequality constraints and Fréchet differentiable equality constraints. Under a suitable constraint qualification (of the Mangasarian-Fromovitz type) an expression for the contingent cone to the feasible set is obtained. As application, necessary conditions of Pareto optimality both Fritz John type and Kuhn-Tucker type are obtained by means of Lagrange multipliers rules.

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