On the convexification procedure for nonconvex and nonsmooth infinite dimensional optimization problems
The paper gives a generalization and modification of a convexification procedure of \textit{D. P. Bertsekas} [J. Optimization Theory Appl. 29, 169- 197 (1979; Zbl 0389.90080)] for infinite dimensional, nonsmooth and nonconvex optimization problems. A nonconvex minimization problem is being transformed into a convex parametrical minimization problem and an additional minimization of an everywhere Fréchet differentiable nonconvex function. The convexification of the nonconvex cost function \(f\) to ensue by means of a strongly convex function \(g\), so that \(f+g\) is also a strongly convex function. One can prove a connection with the duality theory of \textit{J. F. Toland} [J. Math. Anal. Appl. 66, 399-415 (1978; Zbl 0403.90066)] and give a descent method for the original problem.
infinite dimensional, nonsmooth and nonconvex optimization
scientific article; zbMATH DE number 57290