File Exchange

image thumbnail

Constraint-reduced predictor corrector IPM for semidefinite programming

version 1.0.0.0 (16.8 KB) by Sungwoo Park
constraint-reduced predictor-corrector interior point method for semidefinite programming

1 Download

Updated 22 Nov 2015

View License

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.

Cite As

Sungwoo Park (2021). 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. Retrieved .

Comments and Ratings (1)

RMS Danaraj

Thank you for sharing this wonderful code !!!
Great work !!!!
RMS Danaraj
salorajan@gmail.cim

MATLAB Release Compatibility
Created with R2010a
Compatible with any release
Platform Compatibility
Windows macOS Linux

Community Treasure Hunt

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

Start Hunting!