Regularized classical optimality conditions in iterative form for convex optimization problems for distributed Volterra-type systems

ε - optimality conditions for composed convex optimization problems

The aim of the present paper is to provide a formula for the ε subdifferential of f +g ◦h different from the ones which can be found in the existent literature. Further we equivalently characterize this formula by using a so-called closedness type regularity condition expressed by means of the epigraphs of the conjugates of the functions involved. Even more, using the ε subdifferential formula ...

On -optimality Conditions for Convex Set-valued Optimization Problems

In this paper, -subgradients for convex set-valued maps are defined. We prove an existence theorem for -subgradients of convex set-valued maps. Also, we give necessary optimality conditions for an -solution of a convex set-valued optimization problem (CSP). Moreover, using the single-valued function induced from the set-valued map, we obtain theorems describing the -subgradient sum formula for ...

On Optimality Conditions for Abstract Convex Vector Optimization Problems

A sequential optimality condition characterizing the efficient solution without any constraint qualification for an abstract convex vector optimization problem is given in sequential forms using subdifferentials and 2-subdifferentials. Another sequential condition involving only the subdifferentials, but at nearby points to the efficient solution for constraints, is also derived. Moreover, we p...

Global Optimality Conditions for Optimization Problems∗

We establish new necessary and sufficient optimality conditions for optimization problems. In particular, we establish tractable optimality conditions for the problems of minimizing a weakly convex or concave function subject to standard constraints, such as box constraints, binary constraints, and simplex constraints. Our main theoretical tool for establishing these optimality conditions is ab...

Optimality Conditions for Constrained Optimization Problems