Boundary of subdifferentials and calmness moduli in linear semi-infinite optimization
- First Online:
- Cite this article as:
- Cánovas, M.J., Hantoute, A., Parra, J. et al. Optim Lett (2015) 9: 513. doi:10.1007/s11590-014-0767-1
- 172 Downloads
This paper was originally motivated by the problem of providing a point-based formula (only involving the nominal data, and not data in a neighborhood) for estimating the calmness modulus of the optimal set mapping in linear semi-infinite optimization under perturbations of all coefficients. With this aim in mind, the paper establishes as a key tool a basic result on finite-valued convex functions in the \(n\)-dimensional Euclidean space. Specifically, this result provides an upper limit characterization of the boundary of the subdifferential of such a convex function. When applied to the supremum function associated with our constraint system, this characterization allows us to derive an upper estimate for the aimed calmness modulus in linear semi-infinite optimization under the uniqueness of nominal optimal solution.