| Full text | |
| Author(s): |
Amaral, V. S.
;
Andreani, R.
;
Birgin, E. G.
;
Marcondes, D. S.
;
Martinez, J. M.
Total Authors: 5
|
| Document type: | Journal article |
| Source: | Journal of Global Optimization; v. 84, n. 3, p. 35-pg., 2022-04-28. |
| Abstract | |
Coordinate descent methods have considerable impact in global optimization because global (or, at least, almost global) minimization is affordable for low-dimensional problems. Coordinate descent methods with high-order regularized models for smooth nonconvex box-constrained minimization are introduced in this work. High-order stationarity asymptotic convergence and first-order stationarity worst-case evaluation complexity bounds are established. The computer work that is necessary for obtaining first-order epsilon-stationarity with respect to the variables of each coordinate-descent block is O(epsilon(-(p+1)/p)) whereas the computer work forgetting first-order epsilon-stationarity with respect to all the variables simultaneously is O(epsilon(-(p+1))). Numerical examples involving multidimensional scaling problems are presented. The numerical performance of the methods is enhanced by means of coordinate-descent strategies for choosing initial points. (AU) | |
| FAPESP's process: | 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry |
| Grantee: | Francisco Louzada Neto |
| Support Opportunities: | Research Grants - Research, Innovation and Dissemination Centers - RIDC |
| FAPESP's process: | 16/01860-1 - Cutting, packing, lot-sizing, scheduling, routing and location problems and their integration in industrial and logistics settings |
| Grantee: | Reinaldo Morabito Neto |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 18/24293-0 - Computational methods in optimization |
| Grantee: | Sandra Augusta Santos |
| Support Opportunities: | Research Projects - Thematic Grants |