The concerns with finding minima and maxima were for a long time mainly restricted to
mathematical expressions stemming from physical phenomena. The preeminence of being …

In this paper, we study the generalized subdifferentials and the Riemannian gradient
subconsistency that are the basis for non-Lipschitz optimization on embedded submanifolds …

Trust-region methods are a broad class of methods for continuous optimization that found
application in a variety of problems and contexts. In particular, they have been studied and …

We consider nonconvex constrained optimization problems and propose a new approach to
the convergence analysis based on penalty functions. We make use of classical penalty …

In this paper, we study a fully composite formulation of convex optimization problems, which
includes, as a particular case, the problems with functional constraints, max-type …

We consider a degenerate nonsmooth and nonconvex optimization problem for which the
standard constraint qualification such as the generalized Mangasarian--Fromovitz constraint …

Approximations of optimization problems arise in computational procedures and sensitivity
analysis. The resulting effect on solutions can be significant, with even small approximations …