Abstract:
A class of iterative methods – filling methods – for polyhedral approximation of convex compact bodies is introduced and studied. In contrast to augmentation methods, the vertices of the approximating polytope can lie not only on the boundary of the body but also inside it. Within the proposed class, Hausdorff or $H$-methods of filling are singled out, for which the convergence rates (asymptotic and at the initial stage of the approximation) are estimated. For the approximation of nonsmooth convex compact bodies, the resulting convergence rate estimates coincide with those for augmentation $H$-methods.
Key words:
convex sets, polytopes, iterative algorithms, polyhedral approximation, convergence rate of an algorithm.
This publication is cited in the following 4 articles:
Çağin Ararat, Firdevs Ulus, Muhammad Umer, “Convergence Analysis of a Norm Minimization-Based Convex Vector Optimization Algorithm”, SIAM J. Optim., 34:3 (2024), 2700
Shao L., Zhao F., Cong Yu., “Approximation of Convex Bodies By Multiple Objective Optimization and An Application in Reachable Sets”, Optimization, 67:6 (2018), 783–796
V. A. Klyachin, “Approximation of the gradient of a function on the basis of a special
class of triangulations”, Izv. Math., 82:6 (2018), 1136–1147
A. I. Pospelov, “Hausdorff methods for approximating the convex Edgeworth–Pareto hull in integer problems with monotone objectives”, Comput. Math. Math. Phys., 56:8 (2016), 1388–1401