Nonsmooth nonconvex global optimization in a Banach space with a basis
An algorithm is proposed for global minimization of a nonconvex function over a nonconvex (so-called inf-robust) set. The main idea of the algorithm's steps consists in decomposing the level sets into subsets, computing mean values of the objective function over each subset and taking the smallest of them as new level constant. Theoretical convergence of the algorithm is verified.
scientific article; zbMATH DE number 2142451
scientific article