Free Access
Issue
RAIRO-Oper. Res.
Volume 28, Number 4, 1994
Page(s) 329 - 355
DOI https://doi.org/10.1051/ro/1994280403291
Published online 06 February 2017
  • 1. I. ADLER, N. KARMARKAR, M. G. C. RESENDE and G. VEIGA, An implementation of Karmarkar's algorithm for linear programming, Dept. Industrial Engineering and Operations Research, University of California, Berkeley, 1988. [Zbl: 0682.90061] [Google Scholar]
  • 2. K. M. ANSTREICHER, The worst-case step in Karmarkar's algorithm, Mathematics of Ops. Res., 1989, 14, 2, pp. 294-302. [MR: 997036] [Zbl: 0674.90060] [Google Scholar]
  • 3. C. Mc DIARMID, On the improvement per iteration in Karmarkar's method for linear programming, Institute of Economics and Statistics, Oxford University, England, 1986. [Google Scholar]
  • 4. R. B. GOLDSTEIN, Chi-square quantiles, Communications of the A. C. M., 1973, 6, n° 8, pp. 483-485. [Google Scholar]
  • 5. N. KARMARKAR, A new polynomial-time algorithm for linear programming, Combinatorica, 1984, 4, 4, pp. 373-395. [MR: 779900] [Zbl: 0557.90065] [Google Scholar]
  • 6. M. MINOUX, Towards a probabilistic analysis of Karmarkar's algorithm, Colloque Franco-Soviétique de Programmation Mathématique. Marseille, Luminy 8-12 Octobre 1990. [Google Scholar]
  • 7. A. S. NEMIROVSKI, An algorithm of the Karmarkar type, Tekhnicheskaya Kibernetika n°1, 1987, p. 105-118, English Translation in Scripta Technica 1988. [MR: 929639] [Zbl: 0654.90048] [Google Scholar]
  • 8. M. PADBERG, A different convergence proof of the projective method for linear programming, New York University, 1985. [MR: 836260] [Zbl: 0617.90059] [Google Scholar]
  • 9. M. J. D. POWELL, On the number of iterations of Karmarkar's algorithm for linear programming, Mathematical Programming, 1993, 62, pp. 153-197. [MR: 1247612] [Zbl: 0804.90092] [Google Scholar]
  • 10. J. A. TOMLIN, An experimental approach to Karmarkar's projective method for linear programming, Ketron, Inc., Mountain View, CA 94040, 1985. [Zbl: 0634.90044] [Google Scholar]
  • 11. M. J. TODD, Anticipated behaviour of Karmarkar's algorithm, Technical Report n° 879, Cornell University, Ithaca, New York, 14853, 1989. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.