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math.OC2025
Augmented Lagrangian methods for fully convex composite optimization
Alberto De Marchi, Tim Hoheisel, Patrick Mehlitz
This paper is concerned with augmented Lagrangian methods for the treatment of fully convex composite optimization problems. We extend the classical relationship between augmented…
math.OC2025
Approximate stationarity in disjunctive optimization: concepts, qualification conditions, and application to MPCCs
Isabella Käming, Patrick Mehlitz
In this paper, we are concerned with stationarity conditions and qualification conditions for optimization problems with disjunctive constraints. This class covers, among others, o…
math.OC2025
Revisiting implicit variables in mathematical optimization: simplified modeling and a numerical evidence
Patrick Mehlitz
Implicit variables of an optimization problem are used to model variationally challenging feasibility conditions in a tractable way while not entering the objective function. Hence…