Monte Carlo Algorithms for the Detection of Necessary Linear Matrix Inequality Constraints
We reduce the size of large semidefinite programming problems by identifying necessary linear matrix inequalities (LMI's) using Monte Carlo techniques. We describe three algorithms for detecting necessary LMI constraints that extend algorithms used in linear programming to semidefinite programming. We demonstrate that they are beneficial and could serve as tools for a semidefinite programming preprocessor.
|Journal||International Journal of Nonlinear Sciences and Numerical Simulation|
Jibrin, S. (Shafiu), & Pressman, I. (2001). Monte Carlo Algorithms for the Detection of Necessary Linear Matrix Inequality Constraints. International Journal of Nonlinear Sciences and Numerical Simulation, 2(2), 139–153.