Conditioning of convex programs from a primal-dual perspective

Mathematics of Operations Research

Volumn 26, Issue 2, 2001, Pages 206-220

  Pena J ^a  

^a CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

Condition number; Convex programming

Indexed keywords

ALGORITHMS; COMPUTATIONAL METHODS; CONSTRAINT THEORY; ITERATIVE METHODS; LINEAR EQUATIONS; PROBLEM SOLVING; SET THEORY;

CONVEX PROGRAMMING;

LINEAR PROGRAMMING;

EID: 0035351616     PISSN: 0364765X     EISSN: None     Source Type: Journal    
DOI: 10.1287/moor.26.2.206.10551     Document Type: Article

References (19)

1. Condition number complexity of an elementary algorithm for computing a reliable solution of a conic linear system
2. On the complexity of solving sparse symmetric linear programs specified with approximate data
3. Some characterization and properties of the "distance to ill-posedness" and the condition measure of a conic linear system
4. Condition-based complexity of convex optimization in conic linear form via the ellipsoid algorithm
5. Ill-conditioned convex processes and linear inequalities
6. Condition measures and properties of the central trajectory of a linear program
7. Self-scaled barriers and interior-point methods for convex programming
8. Primal-dual interior-point methods for self-scaled cones
9. Understanding the geometry on infeasible perturbations of a conic linear system
10. Computing approximate solutions for conic systems of constraints
11. Some perturbation theory for linear programming
12. Incorporating condition measures into the complexity theory of linear programming
13. Linear programming, complexity theory and elementary functional analysis
14. Condition numbers, the barrier method and the conjugate gradient method
15. Ill-posedness and the complexity of deciding existence of solutions to linear programs
16. On the complexity of linear programming under finite precision arithmetic