Constraint-reduced predictor corrector IPM for semidefinite programming

constraint-reduced predictor-corrector interior point method for semidefinite programming
161 descargas
Actualizado 22 Nov 2015

Ver licencia

Constraint reduction is an essential method because the computational cost of the interior point methods can be effectively saved. Park and O'Leary proposed a constraint-reduced predictor-corrector algorithm for semidefinite programming with polynomial global convergence, but they did not show its superlinear convergence. We first develop a constraint-reduced algorithm for semidefinite programming having both polynomial global and superlinear local convergences. The new algorithm repeats a corrector step to have an iterate tangentially approach a central path, by which superlinear convergence can be achieved.

Citar como

Sungwoo Park (2024). Constraint-reduced predictor corrector IPM for semidefinite programming (https://www.mathworks.com/matlabcentral/fileexchange/54117-constraint-reduced-predictor-corrector-ipm-for-semidefinite-programming), MATLAB Central File Exchange. Recuperado .

Compatibilidad con la versión de MATLAB
Se creó con R2010a
Compatible con cualquier versión
Compatibilidad con las plataformas
Windows macOS Linux
Categorías
Más información sobre Link-Level Simulation en Help Center y MATLAB Answers.

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
Versión Publicado Notas de la versión
1.0.0.0