@article{RMF_2019_94_4_a0,
author = {Zahradn{\'\i}k, Petr},
title = {Line\'arn{\'\i} optimalizace},
journal = {Rozhledy matematicko-fyzik\'aln{\'\i}},
pages = {1--8},
year = {2019},
volume = {94},
number = {4},
language = {cs},
url = {http://geodesic.mathdoc.fr/item/RMF_2019_94_4_a0/}
}
Zahradník, Petr. Lineární optimalizace. Rozhledy matematicko-fyzikální, Tome 94 (2019) no. 4, pp. 1-8. http://geodesic.mathdoc.fr/item/RMF_2019_94_4_a0/
[1] Dantzig, G. B.: Linear Programming and Extensions. United States Air Force Project RAND, R-366-PR, Princeton University Press, Princeton, 1963. | MR
[2] Dantzig, G. B.: A History of Scientific Computing. Origins of the Simplex Method, S. G., Nash (ed.), ACM, New York, NY, 1990, 141–151. | MR
[3] Karp, R. M.: Reducibility among Combinatorial Problems. R. E., Miller, J. W., Thatcher, J. D., Bohlinger (eds.), Springer, Boston, MA, 1972, 85–103. | MR
[4] Karmarkar, N.: A new polynomial-time algorithm for linear programming. Combinatorica, 4 (1984), 4, 373–395. | DOI | MR
[5] Khachiyan, L. G.: Polynomial algorithms in linear programming. USSR Computational Mathematics and Mathematical Physics, 20 (1980), 1, 53–72. | DOI | MR
[6] Land, A. H., Doig, A. G.: An automatic method of solving discrete programming problems. Econometrica, 28 (1960), 3, 497–520. | DOI | MR
[7] Spielman, D. A., Teng, S.-H.: Smoothed analysis of algorithms: Why the simplex algorithm usually takes polynomial time. JACM, 51 (2004), 3, 385–463. | DOI | MR