Sensitivity analysis in multi-parametric strictly convex quadratic optimization

B. Kheirfam

In this paper, we study multi-parametric sensitivity analysis for support set and optimal partition invariancy with simultaneous perturbations in the right-hand-side of constraints and the Linear Term of the objective function of the quadratic programming. We show that the invariancy regions are convex polyhedral sets and we describe the set of admissible parameters by the basis vectors of the lineality space and the extreme directions of the defined cone over appropriate problems, and compare them with the linear optimization case.