On the convex programming approach to linear programming

Authors:
J. R. Rajasekera;S. C. Fang
Affiliations:
AT&T Bell Laboratories, Box 900, Princeton, NJ 08540, USA;North Carolina State University, Box 7913, Raleigh, NC 27695, USA
Venue:
Operations Research Letters
Year:
1991

Citing 2
Cited 0

A new polynomial-time algorithm for linear programming

Combinatorica
On projected Newton barrier methods for linear programming and an equivalence to Karmarkar's projective method

Mathematical Programming: Series A and B

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Abstract

For a general linear program in Karmarkar's standard form, Fang recently proposed a new approach which would find an @e-optimal solution by solving an unconstrained convex dual program. The dual was constructed by applying generalized geometric programming theory to a linear programming problem. In this paper we show that Fang's results can be obtained directly using a simple geometric inequality. The new approach provides a better @e-optimal solution generation scheme in a simpler way.