On the convex programming approach to linear programming

DOI10.1016/0167-6377(91)90001-6zbMath0777.90028OpenAlexW2031770458MaRDI QIDQ1180836

J. R. Rajasekera, Shu-Cherng Fang

Publication date: 27 June 1992

Published in: Operations Research Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-6377(91)90001-6

zbMATH Keywords

generalized geometric programmingKarmarkar's algorithm\(\varepsilon\)-optimal solutionunconstrained convex dual program

Mathematics Subject Classification ID

Convex programming (90C25) Nonlinear programming (90C30) Linear programming (90C05) Computational methods for problems pertaining to operations research and mathematical programming (90-08)

Related Items (6)

Linear programming with entropic perturbation ⋮ A quadratically convergent global algorithm for the linearly-constrained minimum cross-entropy problem ⋮ On the entropic perturbation and exponential penalty methods for linear programming ⋮ An unconstrained dual approach to solving Karmarkar-type linear programs using conventional barrier functions ⋮ An unconstrained convex programming approach to solving convex quadratic programming problems ⋮ Deriving an unconstrained convex program for linear programming

Cites Work

• A new polynomial-time algorithm for linear programming
• Karmarkar's linear programming algorithm and Newton's method
• Unconstrained convex programming approach to linear programming
• An approach to nonlinear programming
• On projected newton barrier methods for linear programming and an equivalence to Karmarkar’s projective method
• Unnamed Item

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