论文信息 - Parallel Implementation of Generalized Newton Method for Solving Large-Scale LP Problems

Parallel Implementation of Generalized Newton Method for Solving Large-Scale LP Problems

The augmented Lagrangian and Generalized Newton methods are used to simultaneously solve the primal and dual linear programming (LP) problems. We propose parallel implementation of the method to solve the primal linear programming problem with very large number (≈ 2 ·106) of nonnegative variables and a large (≈ 2 ·105) number of equality type constraints.

Yuri Evtushenko | A. I. Golikov | Vladimir A. Garanzha | H. M. Nguyen

[1] O. Mangasarian. A Newton Method for Linear Programming , 2004 .

[2] Vipin Kumar,et al. A parallel formulation of interior point algorithms , 1994, Proceedings of Supercomputing '94.

[3] Stephen J. Wright,et al. pPCx: Parallel Software for Linear Programming , 1997, PPSC.

[4] Yuri Evtushenko,et al. Augmented Lagrangian method for large-scale linear programming problems , 2005, Optim. Methods Softw..

[5] A. I. Golikov,et al. Search for normal solutions in linear programming problems , 2000 .

[6] Solution method for large-scale linear programming problems , 2004 .