Nonconvex and nonsmooth approaches for affine chance-constrained stochastic programs
Chance-constrained programs (CCPs) constitute a difficult class of stochastic programs due
to its possible nondifferentiability and nonconvexity even with simple linear random …
to its possible nondifferentiability and nonconvexity even with simple linear random …
Difference-of-Convex approach to chance-constrained Optimal Power Flow modelling the DSO power modulation lever for distribution networks
K Syrtseva, W de Oliveira, S Demassey… - … Energy, Grids and …, 2023 - Elsevier
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 …
the distribution network operation. Short-term operational planning performed by distribution …
Probability maximization via Minkowski functionals: convex representations and tractable resolution
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 …
convex set X, a special case of the chance-constrained optimization problem. Suppose K …
DC Semidefinite programming and cone constrained DC optimization I: theory
MV Dolgopolik - Computational Optimization and Applications, 2022 - Springer
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 …
constrained DC optimization to the case of nonlinear semidefinite programming problems …
DC semidefinite programming and cone constrained DC optimization II: local search methods
MV Dolgopolik - Computational Optimization and Applications, 2023 - Springer
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) …
extensions of the well-known DCA method for solving DC (Difference of Convex functions) …
Minimizing the difference of convex and weakly convex functions via bundle method
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 …
convex and weakly convex functions. This framework covers a vast family of nonsmooth and …
Entry trajectory optimization of lifting-body vehicle by successive difference-of-convex programming
Z Deng, L Liu, Y Wang - Advances in Space Research, 2024 - Elsevier
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 …
due to the need to liberalize the angle of attack and bank angle as control variables, thereby …
Optimality Conditions in Control Problems with Random State Constraints in Probabilistic or Almost Sure Form
C Geiersbach, R Henrion - Mathematics of Operations …, 2024 - pubsonline.informs.org
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 …
state constraints, which are modeled in probabilistic or almost sure form. Although the latter …
The Descent–Ascent Algorithm for DC Programming
P D'Alessandro, M Gaudioso… - INFORMS Journal …, 2024 - pubsonline.informs.org
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 …
of-convex (DC) functions, and it is based on the calculation of a special type of descent …