Hostname: page-component-77c89778f8-gq7q9 Total loading time: 0 Render date: 2024-07-17T14:33:40.109Z Has data issue: false hasContentIssue false

An interior point method for linear programming

Published online by Cambridge University Press:  17 February 2009

M. R. Osborne
Affiliation:
Statistics Research Section, School of Mathematical Sciences, Australian National University, Box 4, GPO, Canberra, A. C. T. 2601, Australia.
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Design of an interior point method for linear programming is discussed, and results of a simulation study reported. Emphasis is put on guessing the optimal vertex at as early a stage as possible.

Type
Research Article
Copyright
Copyright © Australian Mathematical Society 1990

References

[1] Barmes, E. R., “A variation on Karmarkar's algorithm for solving linear programming problems”, Math. Prog. 36 (1986) 174182.CrossRefGoogle Scholar
[2] Brophy, J. F. and Smith, P. W., “Prototyping Karmarkar's algorithm using MATH/PROTRAN”, IMSL Directions 5 (1988) 23.Google Scholar
[3] Gay, D. M., “A variant of Karmarkar's linear programming algorithm for problems in standard form”, Math. Prog. 37 (1987) 8190.CrossRefGoogle Scholar
[4] Karmarkar, N., “A new polynomial-time algorithm for linear programming”, Combinatorica 4 (1984) 373395.Google Scholar
[5] Osborne, M. R., “Dual barrier functions with superfast rates of convergence for the linear programming problem”, J. Austral. Math. Soc. Ser. B 29 (1987) 3958.Google Scholar
[6]Osborne, M. R., Finite algorithms in Optimization and Data Analysis (John Wiley, Chichester,“ 1986).Google Scholar
[7] Renegar, J., “A polynomial-time algorithm, based on Newton's method, for linear programming”, Math. Prog. 40 (1988) 5993.Google Scholar
[8] Ye, Y. and Kojima, M., “Researching optimal dual solutions in Karmarkar's polynomial algorithm for linear programming,” Math. Prog. 39 (1987) 305317.Google Scholar