Impartido por el Dr. Jan-J. Ruckmann (UDLA)
Resumen:
The lecture deals with nonconvex optimization problems in a finite-dimensional space whose feasible sets are defined by infinitely many inequality constraints. These so-called (generalized) semi-infinite optimization problems can be used for the modeling of several practical tasks, e. g. in robotics, design problems, wavelets, approximation problems and others. Several properties of the topological structure of the corresponding feasible sets are discussed and, moreover, necessary and sufficient optimality conditions are analyzed under different assunptions: under appropriate constraint qualifications or by using the directional differentiability of the corresponding optimal value function. Finally, some examples provide a geometrical impression of the results presented.