Strong subdifferentials: theory and applications in nonconvex optimization
Author(s): A. Kabgani & F. Lara
Year: 2022
Title: Strong subdifferentials: theory and applications in nonconvex optimization
Journal: Journal of Global Optimization
pages: 349–368
Doi: https://doi.org/10.1007/s10898-022-01149-9
Cite this article
Kabgani, A., Lara, F. Strong subdifferentials: theory and applications in nonconvex optimization. J Glob Optim 84, 349–368 (2022). https://doi.org/10.1007/s10898-022-01149-9
Abstract
A new subdifferential for dealing with nonconvex functions is provided in the following paper and the usual properties are presented as well. Furthermore, characterizations and optimality conditions for a point to be a solution for the nonconvex minimization problem are given. In particular, new KKT-type optimality conditions for nonconvex nonsmooth constraint optimization problems are developed. Moreover, a relationship with the proximity operator for lower semicontinuous quasiconvex functions is given and, as a consequence, the nonemptiness of this subdifferential for large classes of quasiconvex functions is ensured.