A. Ben-Tal and A. Nemirovski. Robust solutions of Linear Programming problems contaminated with uncertain data. Math. Programming 88(3):411--424, 2000.
K. D. Andersen. A Modified Schur Complement Method for Handling Dense Columns in Interior-Point Methods for Linear Programming. ACM Trans. Math. Software 22(3):348--356, 1996.
A. Ben-Tal and A Nemirovski. Lectures on Modern Convex Optimization: Analysis, Algorithms, and Engineering Applications. MPS/SIAM Series on Optimization. SIAM, 2001.
E. D. Andersen, J. Gondzio, Cs. Meszaros and X. Xu. Implementation of interior point methods for large scale linear programming.
In Interior-point methods of mathematical programming. T. Terlaky, editor(s).Kluwer Academic Publishers,
R. K. Ahuja, T. L. Magnanti and J. B. Orlin. Network flows.
In Optimization. G. L. Nemhauser, A. H. G. Rinnooy Kan and M. J. Todd, editor(s).North Holland, Amsterdam,
M. S. Lobo, M. Fazel, and S. Boyd. Portfolio optimization with linear and fixed transaction costs. 2005.
To appear in Annals of Operations Research. http://www.cds.caltech.edu/~maryam/portfolio.html.
E. D. Andersen, C. Roos and T. Terlaky. On implementing a primal-dual interior-point method for conic quadratic optimization. Math. Programming 95(2), February 2003.
E. D. Andersen and Y. Ye. A computational study of the homogeneous algorithm for large-scale convex optimization. Computational Optimization and Applications 10:243--269, 1998.
E. D. Andersen and K. D. Andersen. The MOSEK interior point optimizer for linear programming: an implementation of the homogeneous algorithm.
In High Performance Optimization Techniques, Proceedings of the HPOPT-II conference. J. B. G. Frenk, C. Roos, T. Terlaky and S. Zhang, editor(s).
forthcoming.
J. L. Kenningon and K. R. Lewis. Generalized networks: The theory of preprocessing and an emperical analysis. INFORMS Journal on Computing 16(2):162--173, 2004.