On the Use of Augmented Lagrangians in the Solution of Generalized Semi-Infinite Min-Max Problems
Computational Optimization and Applications
Generalized semi-infinite programming: A tutorial
Journal of Computational and Applied Mathematics
A lifting method for generalized semi-infinite programs based on lower level Wolfe duality
Computational Optimization and Applications
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We present a general framework for the derivation of first-order optimality conditions in generalized semi-infinite programming. Since in our approach no constraint qualifications are assumed for the index set, we can generalize necessary conditions given by R脙录ckmann and Shapiro (1999) as well as the characterizations of local minimizers of order one, which were derived by Stein and Still (2000). Moreover, we obtain a short proof for Theorem 1.1 in Jongen et al. (1998).For the special case when the so-called lower-level problem is convex, we show how the general optimality conditions can be strengthened, thereby giving a generalization of Theorem 4.2 in R脙录ckmann and Stein (2001). Finally, if the directional derivative of a certain optimal value function exists and is subadditive with respect to the direction, we propose a Mangasarian-Fromovitz-type constraint qualification and show that it implies an Abadie-type constraint qualification.