The exact solution of multiparametric quadratically constrained quadratic programming problems (Q2022221)

The authors consider a multiparametric optimization problem with a convex quadratic objective function, quadratic inequality and linear equality constraints. This problem type is closely related to several uncertainty issues. Using the so-called Basic Sensitivity Theorem and by applying a corresponding active-index-set strategy, they determine the optimal solution in dependence on the values of the parameters. Finally, several illustrative examples are presented.