Ill-Conditioned Convex Processes and Conic Linear Systems
Published Online:1 Nov 1999https://doi.org/10.1287/moor.24.4.829
References
- Adjoint process duality. Math. Oper. Res. (1983) 8:403–434Link, Google Scholar
- Norm duality for convex processes and applications. J. Optim. Theory Appl. (1986) 48:53–64Crossref, Google Scholar
- Some characterizations and properties of the “distance to ill-posedness” and the condition number of a conic linear system. (1998) . Technical report 3862-95-MSA, Sloan School of Management, Massachusetts Institute of Technology, Boston, MAGoogle Scholar
- Condition measures and properties of the central trajectory of a linear program. Math. Programming (1998) 83:1–28Crossref, Google Scholar
- Understanding the geometry of infeasible perturbations of a conic linear system. SIAM J. Optim. (1998) . Technical report, Cornell University, ForthcomingGoogle Scholar
- Incorporating condition measures into the complexity theory of linear programming. SIAM J. Optim. (1995a) 5:506–524Crossref, Google Scholar
- Linear programming, complexity theory and elementary functional analysis. Math. Programming (1995b) 70:279–351Crossref, Google Scholar
- Condition numbers, the barrier method and the conjugate gradient method. SIAM J. Optim. (1996) 6:879–912Crossref, Google Scholar
- Normed convex processes. Trans. Amer. Math. Soc. (1972) 174:127–140Crossref, Google Scholar
- Regularity and stability for convex multivalued functions. Math. Oper. Res. (1976) 1:130–143Link, Google Scholar
- Convex Analysis (1970) (Princeton University Press, Princeton, N.J) Crossref, Google Scholar
- Multifunctions with convex closed graph. Czech. Math. J. (1975) 7:438–441Google Scholar
- Ill-posedness and the complexity of deciding existence of solutions to linear programs. SIAM J. Optim. (1996) 6:549–569Crossref, Google Scholar
- On the complexity of linear programming under finite precision arithmetic. Math. Programming (1998) 80:91–123Crossref, Google Scholar
