| Full text | |
| Author(s): |
Santos, Luiz-Rafael
[1]
;
Villas-Boas, Fernando
[2]
;
Oliveira, Aurelio R. L.
[2]
;
Perin, Clovis
[2]
Total Authors: 4
|
| Affiliation: | [1] Univ Fed Santa Catarina, Dept Math, BR-89065300 Blumenau, SC - Brazil
[2] Univ Estadual Campinas, IMECC, Dept Appl Math, BR-13083859 Campinas, SP - Brazil
Total Affiliations: 2
|
| Document type: | Journal article |
| Source: | COMPUTATIONAL OPTIMIZATION AND APPLICATIONS; v. 73, n. 2, p. 535-574, JUN 2019. |
| Web of Science Citations: | 0 |
| Abstract | |
In this work, we propose a predictor-corrector interior point method for linear programming in a primal-dual context, where the next iterate is chosen by the minimization of a polynomial merit function of three variables: the first is the steplength, the second defines the central path and the third models the weight of a corrector direction. The merit function minimization is performed by restricting it to constraints defined by a neighborhood of the central path that allows wide steps. In this framework, we combine different directions, such as the predictor, the corrector and the centering directions, with the aim of producing a better one. The proposed method generalizes most of predictor-corrector interior point methods, depending on the choice of the variables described above. Convergence analysis of the method is carried out, considering an initial point that has a good practical performance, which results in Q-linear convergence of the iterates with polynomial complexity. Numerical experiments using the Netlib test set are made, which show that this approach is competitive when compared to well established solvers, such as PCx. (AU) | |
| FAPESP's process: | 08/09685-8 - Interior Point Delayed Parameters Choice for Linear Programming |
| Grantee: | Luiz Rafael dos Santos |
| Support Opportunities: | Scholarships in Brazil - Doctorate |
| FAPESP's process: | 10/06822-4 - Efficient solution of large-scale linear and quadratic programming problems |
| Grantee: | Aurelio Ribeiro Leite de Oliveira |
| Support Opportunities: | Research Projects - Thematic Grants |