Equivalence Relations in Convex Optimization

Journal of Applied and Industrial Mathematics - Tập 17 - Trang 339-344 - 2023
E. A. Nurminski1
1Far Eastern Federal University, Vladivostok, Russia

Tóm tắt

Several useful correspondences between general convex optimization problems, support functions, and projection operations are established. These correspondences cover the asymptotic equivalence of projection operations and computation of support functions for general convex sets, hence the same equivalence for general convex optimization problems, and the equivalence between least-norm problems and the problem of regularized convex suplinear optimization.

Tài liệu tham khảo

E. A. Nurminski, “Single-projection procedure for linear optimization,” J. Glob. Optim. 66 (1), 95–110 (2016). E. A. Nurminski, “Projection onto polyhedra in outer representation,” Comput. Math. Math. Phys. 48 (3), 367–375 (2008). S. S. Ablaev, D. V. Makarenko, F. S. Stonyakin, M. S. Alkousa, and I. V. Baran, “Subgradient methods for non-smooth optimization problems with some relaxation of sharp minimum,” Komp’yut. Issled. Model. 14 (2), 473–495 (2022) [in Russian]. T. Bui Hoa, R. S. Burachik, E. A. Nurminski, and M. K. Tam, “Single-projection procedure for infinite dimensional convex optimization problems,” e-Preprint . https://doi.org/10.48550/arXiv.2210.11252 E. A. Nurminski, “Accelerating iterative methods for projection onto polyhedra,” Far East. Math. Collect. 1, 51–62 (1995) [in Russian]. M. V. Dolgopolik, “Exact penalty functions with multidimensional penalty parameter and adaptive penalty updates,” Optim. Lett. 16, 1281–1300 (2022). H. H. Bauschke and J. M. Borwein, “On projection algorithms for solving convex feasibility problems,” SIAM Rev. 38, 367–426 (1996). N. I. M. Gould, “How good are projection methods for convex feasibility problems?” Comput. Optim. Appl. 40, 1–12 (2008). Y. Censor, W. Chen, P. L. Combettes, et al., “On the effectiveness of projection methods for convex feasibility problems with linear inequality constraints,” Comput. Optim. Appl. 51, 1065–1088 (2012). P. R. Johnstone and J. Eckstein, “Convergence rates for projective splitting,” SIAM J. Optim. 29 (3), 1931–1957 (2019).