Cutting planes and column generation techniques with the projective algorithm
Journal of Optimization Theory and Applications
Linear controller design: limits of performance
Linear controller design: limits of performance
Robust and optimal control
A new algorithm for minimizing convex functions over convex sets
Mathematical Programming: Series A and B
Complexity analysis of the analytic center cutting plane method that uses multiple cuts
Mathematical Programming: Series A and B
Interior point algorithms: theory and analysis
Interior point algorithms: theory and analysis
Lectures on modern convex optimization: analysis, algorithms, and engineering applications
Lectures on modern convex optimization: analysis, algorithms, and engineering applications
Complexity Analysis of an Interior Cutting Plane Method for Convex Feasibility Problems
SIAM Journal on Optimization
Multiple Cuts in the Analytic Center Cutting Plane Method
SIAM Journal on Optimization
Optimization Problems over Positive Pseudopolynomial Matrices
SIAM Journal on Matrix Analysis and Applications
Specialized fast algorithms for IQC feasibility and optimization problems
Automatica (Journal of IFAC)
| Hi-index | 22.14 |
Semidefinite programs originating from the Kalman-Yakubovich-Popov lemma are convex optimization problems and there exist polynomial time algorithms that solve them. However, the number of variables is often very large making the computational time extremely long. Algorithms more efficient than general purpose solvers are thus needed. To this end structure exploiting algorithms have been proposed, based on the dual formulation. In this paper a cutting plane algorithm is proposed. In a comparison with a general purpose solver and a structure exploiting solver it is shown that the cutting plane based solver can handle optimization problems of much higher dimension.