Mathematical optimization has always been at the heart of engineering, statistics, and
economics. In these applied domains, optimization concepts and methods have often been …

Chance-constrained programs (CCPs) constitute a difficult class of stochastic programs due
to its possible nondifferentiability and nonconvexity even with simple linear random …

The increasing expansion of renewable energy sources leads to the growth of uncertainty in
the distribution network operation. Short-term operational planning performed by distribution …

In this paper, we consider the maximizing of the probability P ζ∣ ζ∈ K (x) over a closed and
convex set X, a special case of the chance-constrained optimization problem. Suppose K …

In this two-part study, we discuss possible extensions of the main ideas and methods of
constrained DC optimization to the case of nonlinear semidefinite programming problems …

The second part of our study is devoted to a detailed convergence analysis of two
extensions of the well-known DCA method for solving DC (Difference of Convex functions) …

We consider optimization problems with objective and constraint being the difference of
convex and weakly convex functions. This framework covers a vast family of nonsmooth and …

The complexity of the three-dimensional entry trajectory optimization problem has escalated
due to the need to liberalize the angle of attack and bank angle as control variables, thereby …

In this paper, we discuss optimality conditions for optimization problems involving random
state constraints, which are modeled in probabilistic or almost sure form. Although the latter …

We introduce a bundle method for the unconstrained minimization of nonsmooth difference-
of-convex (DC) functions, and it is based on the calculation of a special type of descent …