Abstract
This is the second of a series of two articles en which we study the Karmarkar’s method. In this article we are going to show how can we use sparse matrix theory to get an efficient implementation of the Karmarkar’s process presented in the first article. In phase I of the Karmarkar’s process, it was evident how the size of the technological matrix increased. However, the new matrix has a special structure in which we observed the presence of zero’s blocks that make it a sparse matrix. We will discuss here some techniques to be used with this kind of matrix. Finally we propose a Kamarkar’s variant that takes advantage of this situation.
References
J. F. Avila Herrera (1993) Una implementación eficiente del algoritmo de Karmarkar. Tesis de Maestría ITCR, Cartago, C.R..
J. F. Avila Herrera (1995) “Método de Karmarkar”, Revista de Matemáticas 1
M. S. Bazaraa y J. J. Jarvis (1984) Programación Lineal y Flujo de Redes, 1era Edición. Limusa, México.
M. S. Bazaraa, J. J. Jarvis and H. Sherali (1990)Linear Programming and Network Flows, 2nd Edition. John Wiley & Sons, N.Y..
R. L. Burden y J. D. Douglas (1985) Análisis Numérico. Grupo Editorial Iberoamérica, México.
I. E. Duff and J. K. Reid (1989) Direct Methods for Sparse Matrices. Oxford Science Publications, Oxford.
P. E. Gill, W. Murray, M. A. Saunders and M. H. Wright (1986) Mantaining LU Factors of a General Sparse Matrix. Department of Operations Research, Stanford University, California.
G. H. Golub and C. F. Van Loan (1989) Matrix Computations, 2nd Edition. The Johns Hopkins University Press, USA.
N. Karmarkar (1984) “A new polynomial-time algorithm for Linear Programming”, Combinatorica 4
M. Nuñez y V. Kong (1992) El problema de la Mezcla de Alimentos. Reporte Técnico, ITCR.
Comments
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Copyright (c) 1995 Juan Félix Ávila Herrera